diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..af3dbf1
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,9 @@
+.idea/
+.ipynb_checkpoints/
+**hdf5/
+**.h5
+src/notebooks/junk*
+src/results_analyze/__init__.py
+src/results_analyze/__pycache__/
+src/notebooks/dask-worker-space/
+src/results_analyze/data/credentials.json
\ No newline at end of file
diff --git a/src/notebooks/load_results_files.ipynb b/src/notebooks/load_results_files.ipynb
new file mode 100644
index 0000000..84083fb
--- /dev/null
+++ b/src/notebooks/load_results_files.ipynb
@@ -0,0 +1,1261 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# `load_results_file.py`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "sys.path.append('/home/ayan/Desktop/nexB/gsoc20/scancode-results-analyzer/src')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Simulating Data going into `ResultsDataFrameFile.create_file_level_dataframe` function, which is called by `ResultsDataFramePackage.create_package_level_dataframe`.\n",
+    "Using code snippets from `ResultsDataFramePackage.create_package_level_dataframe`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from results_analyze.load_results_package import ResultsDataFramePackage\n",
+    "results_package = ResultsDataFramePackage()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "SELECT path, content FROM clearcode_cditem WHERE path like '%/scancode/%'OFFSET 0 ROWS FETCH FIRST 20 ROW ONLY;\n"
+     ]
+    }
+   ],
+   "source": [
+    "path_json_dataframe = results_package.convert_records_to_json(20)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Creates `files_dataframe` and breaks at a good example, `file_list` is passed into `ResultsDataFrameFile.create_file_level_dataframe`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "files_dataframe, metadata_dataframe = results_package.modify_package_level_dataframe(path_json_dataframe)\n",
+    "\n",
+    "for package_scan_result in files_dataframe.itertuples():\n",
+    "    file_list = package_scan_result[2]\n",
+    "    if package_scan_result[0] == 1:\n",
+    "        break"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "list"
+      ]
+     },
+     "execution_count": 41,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "type(file_list)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(295,)"
+      ]
+     },
+     "execution_count": 42,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "np.shape(file_list)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "One of the entries inside the list of dicts."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'path': 'ccxt-1.28.76/package.json',\n",
+       " 'type': 'file',\n",
+       " 'name': 'package.json',\n",
+       " 'base_name': 'package',\n",
+       " 'extension': '.json',\n",
+       " 'size': 12024,\n",
+       " 'date': '2020-05-26',\n",
+       " 'sha1': 'a6d104bee2f3a7610bb10ad379bfb6b0d3466f89',\n",
+       " 'md5': '122169b27f6d0a1688a4d21bd3a2d4f6',\n",
+       " 'mime_type': 'text/plain',\n",
+       " 'file_type': 'ASCII text, with very long lines',\n",
+       " 'programming_language': None,\n",
+       " 'is_binary': False,\n",
+       " 'is_text': True,\n",
+       " 'is_archive': False,\n",
+       " 'is_media': False,\n",
+       " 'is_source': False,\n",
+       " 'is_script': False,\n",
+       " 'licenses': [{'key': 'mit',\n",
+       "   'score': 99,\n",
+       "   'name': 'MIT License',\n",
+       "   'short_name': 'MIT License',\n",
+       "   'category': 'Permissive',\n",
+       "   'is_exception': False,\n",
+       "   'owner': 'MIT',\n",
+       "   'homepage_url': 'http://opensource.org/licenses/mit-license.php',\n",
+       "   'text_url': 'http://opensource.org/licenses/mit-license.php',\n",
+       "   'reference_url': 'https://enterprise.dejacode.com/urn/urn:dje:license:mit',\n",
+       "   'spdx_license_key': 'MIT',\n",
+       "   'spdx_url': 'https://spdx.org/licenses/MIT',\n",
+       "   'start_line': 72,\n",
+       "   'end_line': 72,\n",
+       "   'matched_rule': {'identifier': 'mit_34.RULE',\n",
+       "    'license_expression': 'mit',\n",
+       "    'licenses': ['mit'],\n",
+       "    'is_license_text': False,\n",
+       "    'is_license_notice': False,\n",
+       "    'is_license_reference': False,\n",
+       "    'is_license_tag': True,\n",
+       "    'matcher': '2-aho',\n",
+       "    'rule_length': 2,\n",
+       "    'matched_length': 2,\n",
+       "    'match_coverage': 100,\n",
+       "    'rule_relevance': 99},\n",
+       "   'matched_text': 'license\": \"MIT\",'}],\n",
+       " 'license_expressions': ['mit'],\n",
+       " 'holders': [],\n",
+       " 'copyrights': [],\n",
+       " 'authors': [],\n",
+       " 'packages': [],\n",
+       " 'emails': [{'email': 'igor.kroitor@gmail.com',\n",
+       "   'start_line': 69,\n",
+       "   'end_line': 69}],\n",
+       " 'urls': [{'url': 'https://github.com/ccxt/ccxt.git',\n",
+       "   'start_line': 12,\n",
+       "   'end_line': 12},\n",
+       "  {'url': 'https://github.com/kroitor', 'start_line': 70, 'end_line': 70},\n",
+       "  {'url': 'https://github.com/ccxt/ccxt/issues',\n",
+       "   'start_line': 74,\n",
+       "   'end_line': 74},\n",
+       "  {'url': 'https://ccxt.trade/', 'start_line': 76, 'end_line': 76},\n",
+       "  {'url': 'https://opencollective.com/ccxt',\n",
+       "   'start_line': 522,\n",
+       "   'end_line': 522},\n",
+       "  {'url': 'https://opencollective.com/ccxt/logo.txt',\n",
+       "   'start_line': 523,\n",
+       "   'end_line': 523}],\n",
+       " 'is_legal': False,\n",
+       " 'is_manifest': True,\n",
+       " 'is_readme': False,\n",
+       " 'is_top_level': True,\n",
+       " 'is_key_file': True,\n",
+       " 'is_generated': False,\n",
+       " 'is_license_text': False,\n",
+       " 'files_count': 0,\n",
+       " 'dirs_count': 0,\n",
+       " 'size_count': 0,\n",
+       " 'scan_errors': []}"
+      ]
+     },
+     "execution_count": 43,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "file_list[3]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Loads List of Dicts into DataFrame"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from results_analyze.load_results_file import ResultsDataFrameFile\n",
+    "results_file = ResultsDataFrameFile()\n",
+    "file_level_dataframe = pd.DataFrame(file_list)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Viewing DataFrame Columns and their types by calling `DataFrame.dtypes`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "path                    object\n",
+       "type                    object\n",
+       "name                    object\n",
+       "base_name               object\n",
+       "extension               object\n",
+       "size                     int64\n",
+       "date                    object\n",
+       "sha1                    object\n",
+       "md5                     object\n",
+       "mime_type               object\n",
+       "file_type               object\n",
+       "programming_language    object\n",
+       "is_binary                 bool\n",
+       "is_text                   bool\n",
+       "is_archive                bool\n",
+       "is_media                  bool\n",
+       "is_source                 bool\n",
+       "is_script                 bool\n",
+       "licenses                object\n",
+       "license_expressions     object\n",
+       "holders                 object\n",
+       "copyrights              object\n",
+       "authors                 object\n",
+       "packages                object\n",
+       "emails                  object\n",
+       "urls                    object\n",
+       "is_legal                  bool\n",
+       "is_manifest               bool\n",
+       "is_readme                 bool\n",
+       "is_top_level              bool\n",
+       "is_key_file               bool\n",
+       "is_generated              bool\n",
+       "is_license_text           bool\n",
+       "files_count              int64\n",
+       "dirs_count               int64\n",
+       "size_count               int64\n",
+       "scan_errors             object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "file_level_dataframe.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(11, 20)"
+      ]
+     },
+     "execution_count": 63,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "file_level_dataframe.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\u001b[0;31mSignature:\u001b[0m \u001b[0mresults_file\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodify_file_level_dataframe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdataframe_files\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+       "\u001b[0;31mDocstring:\u001b[0m\n",
+       "Takes a File Level DataFrame, drops unnecessary columns, drops all directory rows, drops same files,\n",
+       "drop files with no license detections, and makes sha1 column as the file level Index [Primary Key].\n",
+       "\n",
+       ":param dataframe_files: pd.DataFrame\n",
+       "    File Level DataFrames\n",
+       "\u001b[0;31mFile:\u001b[0m      ~/Desktop/nexB/gsoc20/scancode-results-analyzer/src/results_analyze/load_results_file.py\n",
+       "\u001b[0;31mType:\u001b[0m      method\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "results_file.modify_file_level_dataframe?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "results_file.modify_file_level_dataframe(file_level_dataframe)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(11, 20)"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "file_level_dataframe.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "path                     object\n",
+       "size                      int64\n",
+       "mime_type                object\n",
+       "file_type                object\n",
+       "programming_language     object\n",
+       "is_binary                  bool\n",
+       "is_text                    bool\n",
+       "is_archive                 bool\n",
+       "is_media                   bool\n",
+       "is_source                  bool\n",
+       "is_script                  bool\n",
+       "licenses                 object\n",
+       "is_legal                   bool\n",
+       "is_manifest                bool\n",
+       "is_readme                  bool\n",
+       "is_top_level               bool\n",
+       "is_key_file                bool\n",
+       "is_generated               bool\n",
+       "is_license_text            bool\n",
+       "license_detections_no     int64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "file_level_dataframe.dtypes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Some entries inside `file_level_dataframe`, here `licenses` column contains list of dicts, where list length is number of license detections per file."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>path</th>\n",
+       "      <th>size</th>\n",
+       "      <th>mime_type</th>\n",
+       "      <th>file_type</th>\n",
+       "      <th>programming_language</th>\n",
+       "      <th>is_binary</th>\n",
+       "      <th>is_text</th>\n",
+       "      <th>is_archive</th>\n",
+       "      <th>is_media</th>\n",
+       "      <th>is_source</th>\n",
+       "      <th>is_script</th>\n",
+       "      <th>licenses</th>\n",
+       "      <th>is_legal</th>\n",
+       "      <th>is_manifest</th>\n",
+       "      <th>is_readme</th>\n",
+       "      <th>is_top_level</th>\n",
+       "      <th>is_key_file</th>\n",
+       "      <th>is_generated</th>\n",
+       "      <th>is_license_text</th>\n",
+       "      <th>license_detections_no</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sha1</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
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+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>3be892ba5a4cdc550ac746e257e8e944e79561de</th>\n",
+       "      <td>ccxt-1.28.76/LICENSE.txt</td>\n",
+       "      <td>1068</td>\n",
+       "      <td>text/plain</td>\n",
+       "      <td>UTF-8 Unicode text</td>\n",
+       "      <td>None</td>\n",
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+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>[{'key': 'mit', 'score': 99.4, 'name': 'MIT Li...</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
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+       "      <th>a6d104bee2f3a7610bb10ad379bfb6b0d3466f89</th>\n",
+       "      <td>ccxt-1.28.76/package.json</td>\n",
+       "      <td>12024</td>\n",
+       "      <td>text/plain</td>\n",
+       "      <td>ASCII text, with very long lines</td>\n",
+       "      <td>None</td>\n",
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+       "      <th>15ecee2af9d79cc7c86d42b31b8778faf61e7e35</th>\n",
+       "      <td>ccxt-1.28.76/README.rst</td>\n",
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+       "      <td>text/plain</td>\n",
+       "      <td>UTF-8 Unicode text, with very long lines</td>\n",
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+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>[{'key': 'mit', 'score': 22, 'name': 'MIT Lice...</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
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+       "    </tr>\n",
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+       "      <td>False</td>\n",
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+       "      <td>True</td>\n",
+       "      <td>[{'key': 'mit', 'score': 27, 'name': 'MIT Lice...</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
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+       "      <td>True</td>\n",
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+       "    <tr>\n",
+       "      <th>da97ffed59276dce11663a7ddb468112811debeb</th>\n",
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+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>[{'key': 'mit', 'score': 99.4, 'name': 'MIT Li...</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                                   path  \\\n",
+       "sha1                                                                      \n",
+       "3be892ba5a4cdc550ac746e257e8e944e79561de       ccxt-1.28.76/LICENSE.txt   \n",
+       "a6d104bee2f3a7610bb10ad379bfb6b0d3466f89      ccxt-1.28.76/package.json   \n",
+       "15ecee2af9d79cc7c86d42b31b8778faf61e7e35        ccxt-1.28.76/README.rst   \n",
+       "7e75216e98490df3995164be00d5d6d4ae8d63cf          ccxt-1.28.76/setup.py   \n",
+       "da97ffed59276dce11663a7ddb468112811debeb  ccxt-1.28.76/ccxt/__init__.py   \n",
+       "\n",
+       "                                            size      mime_type  \\\n",
+       "sha1                                                              \n",
+       "3be892ba5a4cdc550ac746e257e8e944e79561de    1068     text/plain   \n",
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+       "\n",
+       "                                                                         file_type  \\\n",
+       "sha1                                                                                 \n",
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+       "\n",
+       "                                         programming_language  is_binary  \\\n",
+       "sha1                                                                       \n",
+       "3be892ba5a4cdc550ac746e257e8e944e79561de                 None      False   \n",
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+       "\n",
+       "                                          is_text  is_archive  is_media  \\\n",
+       "sha1                                                                      \n",
+       "3be892ba5a4cdc550ac746e257e8e944e79561de     True       False     False   \n",
+       "a6d104bee2f3a7610bb10ad379bfb6b0d3466f89     True       False     False   \n",
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+       "da97ffed59276dce11663a7ddb468112811debeb     True       False     False   \n",
+       "\n",
+       "                                          is_source  is_script  \\\n",
+       "sha1                                                             \n",
+       "3be892ba5a4cdc550ac746e257e8e944e79561de      False      False   \n",
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+       "da97ffed59276dce11663a7ddb468112811debeb       True       True   \n",
+       "\n",
+       "                                                                                   licenses  \\\n",
+       "sha1                                                                                          \n",
+       "3be892ba5a4cdc550ac746e257e8e944e79561de  [{'key': 'mit', 'score': 99.4, 'name': 'MIT Li...   \n",
+       "a6d104bee2f3a7610bb10ad379bfb6b0d3466f89  [{'key': 'mit', 'score': 99, 'name': 'MIT Lice...   \n",
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+       "7e75216e98490df3995164be00d5d6d4ae8d63cf  [{'key': 'mit', 'score': 27, 'name': 'MIT Lice...   \n",
+       "da97ffed59276dce11663a7ddb468112811debeb  [{'key': 'mit', 'score': 99.4, 'name': 'MIT Li...   \n",
+       "\n",
+       "                                          is_legal  is_manifest  is_readme  \\\n",
+       "sha1                                                                         \n",
+       "3be892ba5a4cdc550ac746e257e8e944e79561de      True        False      False   \n",
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+       "da97ffed59276dce11663a7ddb468112811debeb     False        False      False   \n",
+       "\n",
+       "                                          is_top_level  is_key_file  \\\n",
+       "sha1                                                                  \n",
+       "3be892ba5a4cdc550ac746e257e8e944e79561de          True         True   \n",
+       "a6d104bee2f3a7610bb10ad379bfb6b0d3466f89          True         True   \n",
+       "15ecee2af9d79cc7c86d42b31b8778faf61e7e35          True         True   \n",
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+       "da97ffed59276dce11663a7ddb468112811debeb         False        False   \n",
+       "\n",
+       "                                          is_generated  is_license_text  \\\n",
+       "sha1                                                                      \n",
+       "3be892ba5a4cdc550ac746e257e8e944e79561de         False             True   \n",
+       "a6d104bee2f3a7610bb10ad379bfb6b0d3466f89         False            False   \n",
+       "15ecee2af9d79cc7c86d42b31b8778faf61e7e35         False            False   \n",
+       "7e75216e98490df3995164be00d5d6d4ae8d63cf         False            False   \n",
+       "da97ffed59276dce11663a7ddb468112811debeb         False            False   \n",
+       "\n",
+       "                                          license_detections_no  \n",
+       "sha1                                                             \n",
+       "3be892ba5a4cdc550ac746e257e8e944e79561de                      1  \n",
+       "a6d104bee2f3a7610bb10ad379bfb6b0d3466f89                      1  \n",
+       "15ecee2af9d79cc7c86d42b31b8778faf61e7e35                      1  \n",
+       "7e75216e98490df3995164be00d5d6d4ae8d63cf                      1  \n",
+       "da97ffed59276dce11663a7ddb468112811debeb                      1  "
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "file_level_dataframe.head(5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These lines takes out all these licenses into `DataFrames`. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lic_level_dataframe = file_level_dataframe.groupby('sha1').licenses.apply(lambda x: pd.DataFrame(x.values[0])).reset_index()\n",
+    "lic_level_dataframe.rename(columns={'level_1': 'lic_det_num'}, inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "These are only license level information in the columns."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "sha1                 object\n",
+       "lic_det_num           int64\n",
+       "key                  object\n",
+       "score               float64\n",
+       "name                 object\n",
+       "short_name           object\n",
+       "category             object\n",
+       "is_exception           bool\n",
+       "owner                object\n",
+       "homepage_url         object\n",
+       "text_url             object\n",
+       "reference_url        object\n",
+       "spdx_license_key     object\n",
+       "spdx_url             object\n",
+       "start_line            int64\n",
+       "end_line              int64\n",
+       "matched_rule         object\n",
+       "matched_text         object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lic_level_dataframe.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 65,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\u001b[0;31mSignature:\u001b[0m \u001b[0mresults_file\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodify_lic_level_dataframe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdataframe_lic\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+       "\u001b[0;31mDocstring:\u001b[0m\n",
+       "Modifies License level DataFrame, from 'matched_rule' dicts, bring information to columns.\n",
+       "Maps Rule Names and other strings to integer values to compress.\n",
+       "\n",
+       ":param dataframe_lic: pd.DataFrame\n",
+       ":return dataframe_lic: pd.DataFrame\n",
+       "\u001b[0;31mFile:\u001b[0m      ~/Desktop/nexB/gsoc20/scancode-results-analyzer/src/results_analyze/load_results_file.py\n",
+       "\u001b[0;31mType:\u001b[0m      method\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "results_file.modify_lic_level_dataframe?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lic_level_dataframe = results_file.modify_lic_level_dataframe(lic_level_dataframe)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 66,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "lic_det_num               int64\n",
+       "key                      object\n",
+       "score                   float64\n",
+       "category                 object\n",
+       "is_exception               bool\n",
+       "start_line                int64\n",
+       "end_line                  int64\n",
+       "matched_text             object\n",
+       "identifier               object\n",
+       "is_license_text            bool\n",
+       "is_license_notice          bool\n",
+       "is_license_reference       bool\n",
+       "is_license_tag             bool\n",
+       "matcher                  object\n",
+       "rule_length               int64\n",
+       "matched_length            int64\n",
+       "match_coverage          float64\n",
+       "rule_relevance            int64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 66,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lic_level_dataframe.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lic_level_dataframe.set_index('sha1', inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Joins License level and File level Dataframes using Join operations, by the primary key `sha1`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "merged_df = file_level_dataframe.join(lic_level_dataframe, lsuffix='_file', rsuffix='_lic')\n",
+    "merged_df.reset_index(inplace=True)\n",
+    "merged_df.set_index(['sha1', 'lic_det_num'], inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Notice how under one file, there can be many license rows, and there are 2 Primary key columns on the left, where there is a one-to-many relationship."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
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+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th>path</th>\n",
+       "      <th>size</th>\n",
+       "      <th>mime_type</th>\n",
+       "      <th>file_type</th>\n",
+       "      <th>programming_language</th>\n",
+       "      <th>is_binary</th>\n",
+       "      <th>is_text</th>\n",
+       "      <th>is_archive</th>\n",
+       "      <th>is_media</th>\n",
+       "      <th>is_source</th>\n",
+       "      <th>...</th>\n",
+       "      <th>identifier</th>\n",
+       "      <th>is_license_text_lic</th>\n",
+       "      <th>is_license_notice</th>\n",
+       "      <th>is_license_reference</th>\n",
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+       "      <th>rule_relevance</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sha1</th>\n",
+       "      <th>lic_det_num</th>\n",
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+       "      <td>False</td>\n",
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+       "      <td>False</td>\n",
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+       "      <td>100.0</td>\n",
+       "      <td>27</td>\n",
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+       "      <td>mit_160.RULE</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>3-seq</td>\n",
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+       "      <td>100</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
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+       "\n",
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+       "3be892ba5a4cdc550ac746e257e8e944e79561de 0                           False   \n",
+       "\n",
+       "                                                      is_license_tag  matcher  \\\n",
+       "sha1                                     lic_det_num                            \n",
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+       "\n",
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+       "\n",
+       "                                                      matched_length  \\\n",
+       "sha1                                     lic_det_num                   \n",
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+       "                                         1                         4   \n",
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+       "3be892ba5a4cdc550ac746e257e8e944e79561de 0                      99.4   \n",
+       "\n",
+       "                                                      rule_relevance  \n",
+       "sha1                                     lic_det_num                  \n",
+       "15ecee2af9d79cc7c86d42b31b8778faf61e7e35 0                        22  \n",
+       "1c3a8a412cca20678559fce34b46686c39a835c0 0                        99  \n",
+       "                                         1                        22  \n",
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+       "3be892ba5a4cdc550ac746e257e8e944e79561de 0                       100  \n",
+       "\n",
+       "[5 rows x 37 columns]"
+      ]
+     },
+     "execution_count": 58,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "merged_df.head(5)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is returned to the `create_package_level_dataframe` function in the package level, where this happends for every row, i.e. every package. They all get merged into One main dataframe."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/src/notebooks/load_results_package.ipynb b/src/notebooks/load_results_package.ipynb
new file mode 100644
index 0000000..063e63c
--- /dev/null
+++ b/src/notebooks/load_results_package.ipynb
@@ -0,0 +1,2039 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import sys\n",
+    "sys.path.append('/home/ayan/Desktop/nexB/gsoc20/scancode-results-analyzer/src')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Import Class `ResultsDataFramePackage` and initialize Object"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from results_analyze.load_results_package import ResultsDataFramePackage\n",
+    "pkg_class = ResultsDataFramePackage()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Fetch Data from Postgres Database, and de-compress memoryview objects - `ResultsDataFramePackage.convert_records_to_json`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>path</th>\n",
+       "      <th>json_content</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>git/github/zzarcon/video-snapshot/revision/b56...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>pypi/pypi/-/ccxt/revision/1.28.76/tool/scancod...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>composer/packagist/motor-cms/motor-core/revisi...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>composer/packagist/lucatume/wp-browser/revisio...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>npm/npmjs/-/aws-sdk/revision/2.687.0/tool/scan...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>npm/npmjs/@types/babel__core/revision/7.1.8/to...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>composer/packagist/topshelfcraft/wordsmith/rev...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>pypi/pypi/-/youtube_dl/revision/2014.01.22.4/t...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>composer/packagist/qingbing/php-file-cache/rev...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>git/github/fnando/browser/revision/9ada0e23745...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>composer/packagist/phpro/grumphp/revision/0.16...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>pypi/pypi/-/yunbk/revision/0.1.59/tool/scancod...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>sourcearchive/mavencentral/org.wso2.siddhi/sid...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>npm/npmjs/-/gatsby-plugin-offline/revision/3.2...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>npm/npmjs/@typescript-eslint/experimental-util...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>npm/npmjs/@juggle/resize-observer/revision/3.2...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>composer/packagist/symfony/thanks/revision/1.2...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>sourcearchive/mavencentral/org.wso2.carbon.ide...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>pypi/pypi/-/uiautomator2/revision/0.1.4.dev30/...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>npm/npmjs/@storybook/addons/revision/6.0.0-bet...</td>\n",
+       "      <td>{'_metadata': {'type': 'scancode', 'url': 'cd:...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                 path  \\\n",
+       "0   git/github/zzarcon/video-snapshot/revision/b56...   \n",
+       "1   pypi/pypi/-/ccxt/revision/1.28.76/tool/scancod...   \n",
+       "2   composer/packagist/motor-cms/motor-core/revisi...   \n",
+       "3   composer/packagist/lucatume/wp-browser/revisio...   \n",
+       "4   npm/npmjs/-/aws-sdk/revision/2.687.0/tool/scan...   \n",
+       "5   npm/npmjs/@types/babel__core/revision/7.1.8/to...   \n",
+       "6   composer/packagist/topshelfcraft/wordsmith/rev...   \n",
+       "7   pypi/pypi/-/youtube_dl/revision/2014.01.22.4/t...   \n",
+       "8   composer/packagist/qingbing/php-file-cache/rev...   \n",
+       "9   git/github/fnando/browser/revision/9ada0e23745...   \n",
+       "10  composer/packagist/phpro/grumphp/revision/0.16...   \n",
+       "11  pypi/pypi/-/yunbk/revision/0.1.59/tool/scancod...   \n",
+       "12  sourcearchive/mavencentral/org.wso2.siddhi/sid...   \n",
+       "13  npm/npmjs/-/gatsby-plugin-offline/revision/3.2...   \n",
+       "14  npm/npmjs/@typescript-eslint/experimental-util...   \n",
+       "15  npm/npmjs/@juggle/resize-observer/revision/3.2...   \n",
+       "16  composer/packagist/symfony/thanks/revision/1.2...   \n",
+       "17  sourcearchive/mavencentral/org.wso2.carbon.ide...   \n",
+       "18  pypi/pypi/-/uiautomator2/revision/0.1.4.dev30/...   \n",
+       "19  npm/npmjs/@storybook/addons/revision/6.0.0-bet...   \n",
+       "\n",
+       "                                         json_content  \n",
+       "0   {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "1   {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "2   {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "3   {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "4   {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "5   {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "6   {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "7   {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "8   {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "9   {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "10  {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "11  {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "12  {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "13  {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "14  {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "15  {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "16  {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "17  {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "18  {'_metadata': {'type': 'scancode', 'url': 'cd:...  \n",
+       "19  {'_metadata': {'type': 'scancode', 'url': 'cd:...  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "path_json_dataframe = pkg_class.convert_records_to_json(20)\n",
+    "path_json_dataframe"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "dict"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "type(path_json_dataframe['json_content'][0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'type': 'scancode',\n",
+       " 'url': 'cd:/git/github/zzarcon/video-snapshot/b56386f225a2d082b1e56a0f24cfda595798c654',\n",
+       " 'fetchedAt': '2019-04-17T14:18:35.855Z',\n",
+       " 'links': {'self': {'href': 'urn:git:github:zzarcon:video-snapshot:revision:b56386f225a2d082b1e56a0f24cfda595798c654:tool:scancode:3.2.2',\n",
+       "   'type': 'resource'},\n",
+       "  'siblings': {'href': 'urn:git:github:zzarcon:video-snapshot:revision:b56386f225a2d082b1e56a0f24cfda595798c654:tool:scancode',\n",
+       "   'type': 'collection'}},\n",
+       " 'schemaVersion': '3.2.2',\n",
+       " 'toolVersion': '3.0.2',\n",
+       " 'contentType': 'application/json',\n",
+       " 'releaseDate': '2018-02-11T09:13:12.000Z',\n",
+       " 'processedAt': '2019-04-17T14:19:10.672Z'}"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "path_json_dataframe['json_content'][0]['_metadata']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[{'tool_name': 'scancode-toolkit',\n",
+       "  'tool_version': '3.0.2',\n",
+       "  'options': {'input': '/tmp/cd-rBieg5/video-snapshot',\n",
+       "   '--classify': True,\n",
+       "   '--copyright': True,\n",
+       "   '--email': True,\n",
+       "   '--generated': True,\n",
+       "   '--info': True,\n",
+       "   '--is-license-text': True,\n",
+       "   '--json-pp': '/tmp/cd-4wjkc3',\n",
+       "   '--license': True,\n",
+       "   '--license-clarity-score': True,\n",
+       "   '--license-diag': True,\n",
+       "   '--license-text': True,\n",
+       "   '--package': True,\n",
+       "   '--processes': '2',\n",
+       "   '--strip-root': True,\n",
+       "   '--summary': True,\n",
+       "   '--summary-key-files': True,\n",
+       "   '--timeout': '1000.0',\n",
+       "   '--url': True},\n",
+       "  'notice': 'Generated with ScanCode and provided on an \"AS IS\" BASIS, WITHOUT WARRANTIES\\nOR CONDITIONS OF ANY KIND, either express or implied. No content created from\\nScanCode should be considered or used as legal advice. Consult an Attorney\\nfor any legal advice.\\nScanCode is a free software code scanning tool from nexB Inc. and others.\\nVisit https://github.com/nexB/scancode-toolkit/ for support and download.',\n",
+       "  'start_timestamp': '2019-04-17T141841.687970',\n",
+       "  'end_timestamp': '2019-04-17T141909.130763',\n",
+       "  'message': None,\n",
+       "  'errors': [],\n",
+       "  'extra_data': {'files_count': 14}}]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "path_json_dataframe['json_content'][0]['content']['headers']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "path            object\n",
+       "json_content    object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "path_json_dataframe.dtypes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Package level Dataframe is modified, and new columns are added from dicts inside the column"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\u001b[0;31mSignature:\u001b[0m \u001b[0mpkg_class\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodify_package_level_dataframe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmetadata_dataframe\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+       "\u001b[0;31mDocstring:\u001b[0m\n",
+       "This function is applied to one column of a Dataframe containing json dicts, at once, to perform\n",
+       "vectorized data retrieval. Then convert this row of values/lists to dataframes.\n",
+       "The DataFrames column name is the `name_value`.\n",
+       "\n",
+       ":param metadata_dataframe : pd.DataFrame\n",
+       "\n",
+       ":returns\n",
+       "files_dataframe : pd.DataFrame\n",
+       "    DataFrame, containing a two columns, which has the path_string in one, and has a list of dicts in each row\n",
+       "    of the other column, which is list of file-level dicts.\n",
+       "metadata_dataframe : pd.DataFrame\n",
+       "    DataFrame, containing a new column for the value/list, from inside the JSON dict.\n",
+       "\u001b[0;31mFile:\u001b[0m      ~/Desktop/nexB/gsoc20/scancode-results-analyzer/src/results_analyze/load_results_package.py\n",
+       "\u001b[0;31mType:\u001b[0m      method\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pkg_class.modify_package_level_dataframe?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "files_dataframe, metadata_dataframe = pkg_class.modify_package_level_dataframe(path_json_dataframe)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "path                                                       object\n",
+       "score                                                       int64\n",
+       "has_declared_license_in_key_files                            bool\n",
+       "file_level_license_and_copyright_coverage                 float64\n",
+       "has_consistent_key_and_file_level_licenses                   bool\n",
+       "is_using_only_spdx_licenses                                  bool\n",
+       "has_full_text_for_all_licenses                               bool\n",
+       "TimeIndex                                     datetime64[ns, UTC]\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "metadata_dataframe.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "TimeIndex    datetime64[ns, UTC]\n",
+       "Files                     object\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "files_dataframe.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "list"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "type(path_json_dataframe['json_content'][0]['content']['files'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'path': 'LICENSE',\n",
+       " 'type': 'file',\n",
+       " 'name': 'LICENSE',\n",
+       " 'base_name': 'LICENSE',\n",
+       " 'extension': '',\n",
+       " 'size': 1070,\n",
+       " 'date': '2019-04-17',\n",
+       " 'sha1': 'c31f1358e9e15586333a3a91298e770a9d360867',\n",
+       " 'md5': '2f0943b127960f438881e0550ddf9fa1',\n",
+       " 'mime_type': 'text/plain',\n",
+       " 'file_type': 'ASCII text',\n",
+       " 'programming_language': None,\n",
+       " 'is_binary': False,\n",
+       " 'is_text': True,\n",
+       " 'is_archive': False,\n",
+       " 'is_media': False,\n",
+       " 'is_source': False,\n",
+       " 'is_script': False,\n",
+       " 'licenses': [{'key': 'mit',\n",
+       "   'score': 99.4,\n",
+       "   'name': 'MIT License',\n",
+       "   'short_name': 'MIT License',\n",
+       "   'category': 'Permissive',\n",
+       "   'is_exception': False,\n",
+       "   'owner': 'MIT',\n",
+       "   'homepage_url': 'http://opensource.org/licenses/mit-license.php',\n",
+       "   'text_url': 'http://opensource.org/licenses/mit-license.php',\n",
+       "   'reference_url': 'https://enterprise.dejacode.com/urn/urn:dje:license:mit',\n",
+       "   'spdx_license_key': 'MIT',\n",
+       "   'spdx_url': 'https://spdx.org/licenses/MIT',\n",
+       "   'start_line': 1,\n",
+       "   'end_line': 21,\n",
+       "   'matched_rule': {'identifier': 'mit_160.RULE',\n",
+       "    'license_expression': 'mit',\n",
+       "    'licenses': ['mit'],\n",
+       "    'is_license_text': True,\n",
+       "    'is_license_notice': False,\n",
+       "    'is_license_reference': False,\n",
+       "    'is_license_tag': False,\n",
+       "    'matcher': '3-seq',\n",
+       "    'rule_length': 167,\n",
+       "    'matched_length': 166,\n",
+       "    'match_coverage': 99.4,\n",
+       "    'rule_relevance': 100},\n",
+       "   'matched_text': 'MIT License\\n\\nCopyright ([c]) [2018] [Hector] [Zarco] \\n\\nPermission is hereby granted, free of charge, to any person obtaining a copy\\nof this software and associated documentation files (the \"Software\"), to deal\\nin the Software without restriction, including without limitation the rights\\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\\ncopies of the Software, and to permit persons to whom the Software is\\nfurnished to do so, subject to the following conditions:\\n\\nThe above copyright notice and this permission notice shall be included in all\\ncopies or substantial portions of the Software.\\n\\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\\nSOFTWARE.'}],\n",
+       " 'license_expressions': ['mit'],\n",
+       " 'holders': [{'value': 'Hector Zarco', 'start_line': 3, 'end_line': 3}],\n",
+       " 'copyrights': [{'value': 'Copyright (c) 2018 Hector Zarco',\n",
+       "   'start_line': 3,\n",
+       "   'end_line': 3}],\n",
+       " 'authors': [],\n",
+       " 'packages': [],\n",
+       " 'emails': [],\n",
+       " 'urls': [],\n",
+       " 'is_legal': True,\n",
+       " 'is_manifest': False,\n",
+       " 'is_readme': False,\n",
+       " 'is_top_level': True,\n",
+       " 'is_key_file': True,\n",
+       " 'is_generated': False,\n",
+       " 'is_license_text': True,\n",
+       " 'files_count': 0,\n",
+       " 'dirs_count': 0,\n",
+       " 'size_count': 0,\n",
+       " 'scan_errors': []}"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "files_dataframe['Files'][0][2]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<results_analyze.load_results_file.ResultsDataFrameFile at 0x7f39b98a5eb8>"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pkg_class.results_file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "file_level_dataframes_list = []\n",
+    "for package_scan_result in files_dataframe.itertuples():\n",
+    "    file_level_dataframe = pkg_class.results_file.create_file_level_dataframe(package_scan_result[2])\n",
+    "    file_level_dataframes_list.append(file_level_dataframe)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Columns of File level DataFrame"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "path                      object\n",
+       "size                       int64\n",
+       "mime_type                 object\n",
+       "file_type                 object\n",
+       "programming_language      object\n",
+       "is_binary                   bool\n",
+       "is_text                     bool\n",
+       "is_archive                  bool\n",
+       "is_media                    bool\n",
+       "is_source                   bool\n",
+       "is_script                   bool\n",
+       "licenses                  object\n",
+       "is_legal                    bool\n",
+       "is_manifest                 bool\n",
+       "is_readme                   bool\n",
+       "is_top_level                bool\n",
+       "is_key_file                 bool\n",
+       "is_generated                bool\n",
+       "is_license_text_file        bool\n",
+       "license_detections_no      int64\n",
+       "key                       object\n",
+       "score                    float64\n",
+       "category                  object\n",
+       "is_exception                bool\n",
+       "start_line                 int64\n",
+       "end_line                   int64\n",
+       "matched_text              object\n",
+       "identifier                object\n",
+       "is_license_text_lic         bool\n",
+       "is_license_notice           bool\n",
+       "is_license_reference        bool\n",
+       "is_license_tag              bool\n",
+       "matcher                   object\n",
+       "rule_length                int64\n",
+       "matched_length             int64\n",
+       "match_coverage           float64\n",
+       "rule_relevance             int64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "file_level_dataframe.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th>path</th>\n",
+       "      <th>size</th>\n",
+       "      <th>mime_type</th>\n",
+       "      <th>file_type</th>\n",
+       "      <th>programming_language</th>\n",
+       "      <th>is_binary</th>\n",
+       "      <th>is_text</th>\n",
+       "      <th>is_archive</th>\n",
+       "      <th>is_media</th>\n",
+       "      <th>is_source</th>\n",
+       "      <th>...</th>\n",
+       "      <th>identifier</th>\n",
+       "      <th>is_license_text_lic</th>\n",
+       "      <th>is_license_notice</th>\n",
+       "      <th>is_license_reference</th>\n",
+       "      <th>is_license_tag</th>\n",
+       "      <th>matcher</th>\n",
+       "      <th>rule_length</th>\n",
+       "      <th>matched_length</th>\n",
+       "      <th>match_coverage</th>\n",
+       "      <th>rule_relevance</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>sha1</th>\n",
+       "      <th>lic_det_num</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>b052b1693074fa80a08f8b97e7013b4ffa903ea2</th>\n",
+       "      <th>0</th>\n",
+       "      <td>package/LICENSE</td>\n",
+       "      <td>1097</td>\n",
+       "      <td>text/plain</td>\n",
+       "      <td>ASCII text</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>...</td>\n",
+       "      <td>mit_26.RULE</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>3-seq</td>\n",
+       "      <td>167</td>\n",
+       "      <td>166</td>\n",
+       "      <td>99.4</td>\n",
+       "      <td>100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>ba9f5f050b26533835c3d9c95d6ee020ffba40fc</th>\n",
+       "      <th>0</th>\n",
+       "      <td>package/package.json</td>\n",
+       "      <td>1376</td>\n",
+       "      <td>text/plain</td>\n",
+       "      <td>ASCII text</td>\n",
+       "      <td>None</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>...</td>\n",
+       "      <td>mit_34.RULE</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>False</td>\n",
+       "      <td>True</td>\n",
+       "      <td>2-aho</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>100.0</td>\n",
+       "      <td>99</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>2 rows × 37 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                                      path  \\\n",
+       "sha1                                     lic_det_num                         \n",
+       "b052b1693074fa80a08f8b97e7013b4ffa903ea2 0                 package/LICENSE   \n",
+       "ba9f5f050b26533835c3d9c95d6ee020ffba40fc 0            package/package.json   \n",
+       "\n",
+       "                                                      size   mime_type  \\\n",
+       "sha1                                     lic_det_num                     \n",
+       "b052b1693074fa80a08f8b97e7013b4ffa903ea2 0            1097  text/plain   \n",
+       "ba9f5f050b26533835c3d9c95d6ee020ffba40fc 0            1376  text/plain   \n",
+       "\n",
+       "                                                       file_type  \\\n",
+       "sha1                                     lic_det_num               \n",
+       "b052b1693074fa80a08f8b97e7013b4ffa903ea2 0            ASCII text   \n",
+       "ba9f5f050b26533835c3d9c95d6ee020ffba40fc 0            ASCII text   \n",
+       "\n",
+       "                                                     programming_language  \\\n",
+       "sha1                                     lic_det_num                        \n",
+       "b052b1693074fa80a08f8b97e7013b4ffa903ea2 0                           None   \n",
+       "ba9f5f050b26533835c3d9c95d6ee020ffba40fc 0                           None   \n",
+       "\n",
+       "                                                      is_binary  is_text  \\\n",
+       "sha1                                     lic_det_num                       \n",
+       "b052b1693074fa80a08f8b97e7013b4ffa903ea2 0                False     True   \n",
+       "ba9f5f050b26533835c3d9c95d6ee020ffba40fc 0                False     True   \n",
+       "\n",
+       "                                                      is_archive  is_media  \\\n",
+       "sha1                                     lic_det_num                         \n",
+       "b052b1693074fa80a08f8b97e7013b4ffa903ea2 0                 False     False   \n",
+       "ba9f5f050b26533835c3d9c95d6ee020ffba40fc 0                 False     False   \n",
+       "\n",
+       "                                                      is_source  ...  \\\n",
+       "sha1                                     lic_det_num             ...   \n",
+       "b052b1693074fa80a08f8b97e7013b4ffa903ea2 0                False  ...   \n",
+       "ba9f5f050b26533835c3d9c95d6ee020ffba40fc 0                False  ...   \n",
+       "\n",
+       "                                                       identifier  \\\n",
+       "sha1                                     lic_det_num                \n",
+       "b052b1693074fa80a08f8b97e7013b4ffa903ea2 0            mit_26.RULE   \n",
+       "ba9f5f050b26533835c3d9c95d6ee020ffba40fc 0            mit_34.RULE   \n",
+       "\n",
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+       "sha1                                     lic_det_num                       \n",
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+       "ba9f5f050b26533835c3d9c95d6ee020ffba40fc 0                         False   \n",
+       "\n",
+       "                                                      is_license_notice  \\\n",
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+       "\n",
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+       "\n",
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+       "ba9f5f050b26533835c3d9c95d6ee020ffba40fc 0                      True    2-aho   \n",
+       "\n",
+       "                                                      rule_length  \\\n",
+       "sha1                                     lic_det_num                \n",
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+       "\n",
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+       "\n",
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+       "sha1                                     lic_det_num                   \n",
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+       "\n",
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+       "sha1                                     lic_det_num                  \n",
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+       "\n",
+       "[2 rows x 37 columns]"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "file_level_dataframe.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "list_file_level_keys = list(files_dataframe['TimeIndex'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[Timestamp('2019-04-17 14:19:10.672000+0000', tz='UTC'),\n",
+       " Timestamp('2020-05-26 21:20:17.862000+0000', tz='UTC'),\n",
+       " Timestamp('2019-10-10 21:19:38.969000+0000', tz='UTC'),\n",
+       " Timestamp('2020-06-02 13:30:17.825000+0000', tz='UTC'),\n",
+       " Timestamp('2020-06-01 23:24:15.483000+0000', tz='UTC'),\n",
+       " Timestamp('2020-06-02 00:06:35.792000+0000', tz='UTC'),\n",
+       " Timestamp('2019-09-23 12:12:28.640000+0000', tz='UTC'),\n",
+       " Timestamp('2020-05-25 23:05:57.708000+0000', tz='UTC'),\n",
+       " Timestamp('2019-09-26 01:02:47.736000+0000', tz='UTC'),\n",
+       " Timestamp('2020-06-02 00:48:46.874000+0000', tz='UTC'),\n",
+       " Timestamp('2019-09-23 18:09:05.285000+0000', tz='UTC'),\n",
+       " Timestamp('2019-05-08 08:53:53.642000+0000', tz='UTC'),\n",
+       " Timestamp('2019-05-01 09:44:02.351000+0000', tz='UTC'),\n",
+       " Timestamp('2020-06-02 12:51:26.231000+0000', tz='UTC'),\n",
+       " Timestamp('2020-06-01 18:54:29.146000+0000', tz='UTC'),\n",
+       " Timestamp('2020-06-02 06:58:36.733000+0000', tz='UTC'),\n",
+       " Timestamp('2020-05-30 10:06:37.472000+0000', tz='UTC'),\n",
+       " Timestamp('2019-05-02 14:20:09.135000+0000', tz='UTC'),\n",
+       " Timestamp('2019-04-25 03:04:31.391000+0000', tz='UTC'),\n",
+       " Timestamp('2020-05-31 23:04:03.965000+0000', tz='UTC')]"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "list_file_level_keys"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "main_dataframe = pd.concat(file_level_dataframes_list,keys=list_file_level_keys)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Notice how under one package, there can be many files, and under one file, there can be many license rows, and there are 3 Primary key columns on the left, where there is a one-to-many relationship from left to right."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
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+       "2020-06-02 13:30:17.825000+00:00 10117bb7a0b195dc7b6aeaae78be69c10fa7d620 0                         Python   \n",
+       "                                                                          1                         Python   \n",
+       "                                 254d7d285416df46733e9541e4da21fc498d3502 0                           None   \n",
+       "                                 4b6af7167d38d0751614ad390908dc4a8e0ef652 0                            PHP   \n",
+       "\n",
+       "                                                                                       is_binary  \\\n",
+       "                                 sha1                                     lic_det_num              \n",
+       "2019-04-17 14:19:10.672000+00:00 c31f1358e9e15586333a3a91298e770a9d360867 0                False   \n",
+       "                                 e5dad7813f1edf787936eedfa92c421bf28080c3 0                False   \n",
+       "2020-05-26 21:20:17.862000+00:00 15ecee2af9d79cc7c86d42b31b8778faf61e7e35 0                False   \n",
+       "                                 1c3a8a412cca20678559fce34b46686c39a835c0 0                False   \n",
+       "                                                                          1                False   \n",
+       "                                                                          2                False   \n",
+       "                                 3be892ba5a4cdc550ac746e257e8e944e79561de 0                False   \n",
+       "                                 3d5143b5fffba7880c3c2d10d73ae39740dbdd2c 0                False   \n",
+       "                                 4828905332706cdfebe3dfe9f699bb6616abfd76 0                False   \n",
+       "                                 7e75216e98490df3995164be00d5d6d4ae8d63cf 0                False   \n",
+       "                                 9d5dc47d7b122dbfb7005e627a352ca001dddb73 0                False   \n",
+       "                                 a5fddef68a032cd03b957cca5076c2244480a34b 0                False   \n",
+       "                                 a6d104bee2f3a7610bb10ad379bfb6b0d3466f89 0                False   \n",
+       "                                 abcd264d3854a8b5cc987f265fb581b8c59ebe50 0                False   \n",
+       "                                 da97ffed59276dce11663a7ddb468112811debeb 0                False   \n",
+       "2019-10-10 21:19:38.969000+00:00 cdff21aa9a0f6aa5341e1c971146d1fc30febd1f 0                False   \n",
+       "2020-06-02 13:30:17.825000+00:00 10117bb7a0b195dc7b6aeaae78be69c10fa7d620 0                False   \n",
+       "                                                                          1                False   \n",
+       "                                 254d7d285416df46733e9541e4da21fc498d3502 0                False   \n",
+       "                                 4b6af7167d38d0751614ad390908dc4a8e0ef652 0                False   \n",
+       "\n",
+       "                                                                                       is_text  \\\n",
+       "                                 sha1                                     lic_det_num            \n",
+       "2019-04-17 14:19:10.672000+00:00 c31f1358e9e15586333a3a91298e770a9d360867 0               True   \n",
+       "                                 e5dad7813f1edf787936eedfa92c421bf28080c3 0               True   \n",
+       "2020-05-26 21:20:17.862000+00:00 15ecee2af9d79cc7c86d42b31b8778faf61e7e35 0               True   \n",
+       "                                 1c3a8a412cca20678559fce34b46686c39a835c0 0               True   \n",
+       "                                                                          1               True   \n",
+       "                                                                          2               True   \n",
+       "                                 3be892ba5a4cdc550ac746e257e8e944e79561de 0               True   \n",
+       "                                 3d5143b5fffba7880c3c2d10d73ae39740dbdd2c 0               True   \n",
+       "                                 4828905332706cdfebe3dfe9f699bb6616abfd76 0               True   \n",
+       "                                 7e75216e98490df3995164be00d5d6d4ae8d63cf 0               True   \n",
+       "                                 9d5dc47d7b122dbfb7005e627a352ca001dddb73 0               True   \n",
+       "                                 a5fddef68a032cd03b957cca5076c2244480a34b 0               True   \n",
+       "                                 a6d104bee2f3a7610bb10ad379bfb6b0d3466f89 0               True   \n",
+       "                                 abcd264d3854a8b5cc987f265fb581b8c59ebe50 0               True   \n",
+       "                                 da97ffed59276dce11663a7ddb468112811debeb 0               True   \n",
+       "2019-10-10 21:19:38.969000+00:00 cdff21aa9a0f6aa5341e1c971146d1fc30febd1f 0               True   \n",
+       "2020-06-02 13:30:17.825000+00:00 10117bb7a0b195dc7b6aeaae78be69c10fa7d620 0               True   \n",
+       "                                                                          1               True   \n",
+       "                                 254d7d285416df46733e9541e4da21fc498d3502 0               True   \n",
+       "                                 4b6af7167d38d0751614ad390908dc4a8e0ef652 0               True   \n",
+       "\n",
+       "                                                                                       is_archive  \\\n",
+       "                                 sha1                                     lic_det_num               \n",
+       "2019-04-17 14:19:10.672000+00:00 c31f1358e9e15586333a3a91298e770a9d360867 0                 False   \n",
+       "                                 e5dad7813f1edf787936eedfa92c421bf28080c3 0                 False   \n",
+       "2020-05-26 21:20:17.862000+00:00 15ecee2af9d79cc7c86d42b31b8778faf61e7e35 0                 False   \n",
+       "                                 1c3a8a412cca20678559fce34b46686c39a835c0 0                 False   \n",
+       "                                                                          1                 False   \n",
+       "                                                                          2                 False   \n",
+       "                                 3be892ba5a4cdc550ac746e257e8e944e79561de 0                 False   \n",
+       "                                 3d5143b5fffba7880c3c2d10d73ae39740dbdd2c 0                 False   \n",
+       "                                 4828905332706cdfebe3dfe9f699bb6616abfd76 0                 False   \n",
+       "                                 7e75216e98490df3995164be00d5d6d4ae8d63cf 0                 False   \n",
+       "                                 9d5dc47d7b122dbfb7005e627a352ca001dddb73 0                 False   \n",
+       "                                 a5fddef68a032cd03b957cca5076c2244480a34b 0                 False   \n",
+       "                                 a6d104bee2f3a7610bb10ad379bfb6b0d3466f89 0                 False   \n",
+       "                                 abcd264d3854a8b5cc987f265fb581b8c59ebe50 0                 False   \n",
+       "                                 da97ffed59276dce11663a7ddb468112811debeb 0                 False   \n",
+       "2019-10-10 21:19:38.969000+00:00 cdff21aa9a0f6aa5341e1c971146d1fc30febd1f 0                 False   \n",
+       "2020-06-02 13:30:17.825000+00:00 10117bb7a0b195dc7b6aeaae78be69c10fa7d620 0                 False   \n",
+       "                                                                          1                 False   \n",
+       "                                 254d7d285416df46733e9541e4da21fc498d3502 0                 False   \n",
+       "                                 4b6af7167d38d0751614ad390908dc4a8e0ef652 0                 False   \n",
+       "\n",
+       "                                                                                       is_media  \\\n",
+       "                                 sha1                                     lic_det_num             \n",
+       "2019-04-17 14:19:10.672000+00:00 c31f1358e9e15586333a3a91298e770a9d360867 0               False   \n",
+       "                                 e5dad7813f1edf787936eedfa92c421bf28080c3 0               False   \n",
+       "2020-05-26 21:20:17.862000+00:00 15ecee2af9d79cc7c86d42b31b8778faf61e7e35 0               False   \n",
+       "                                 1c3a8a412cca20678559fce34b46686c39a835c0 0               False   \n",
+       "                                                                          1               False   \n",
+       "                                                                          2               False   \n",
+       "                                 3be892ba5a4cdc550ac746e257e8e944e79561de 0               False   \n",
+       "                                 3d5143b5fffba7880c3c2d10d73ae39740dbdd2c 0               False   \n",
+       "                                 4828905332706cdfebe3dfe9f699bb6616abfd76 0               False   \n",
+       "                                 7e75216e98490df3995164be00d5d6d4ae8d63cf 0               False   \n",
+       "                                 9d5dc47d7b122dbfb7005e627a352ca001dddb73 0               False   \n",
+       "                                 a5fddef68a032cd03b957cca5076c2244480a34b 0               False   \n",
+       "                                 a6d104bee2f3a7610bb10ad379bfb6b0d3466f89 0               False   \n",
+       "                                 abcd264d3854a8b5cc987f265fb581b8c59ebe50 0               False   \n",
+       "                                 da97ffed59276dce11663a7ddb468112811debeb 0               False   \n",
+       "2019-10-10 21:19:38.969000+00:00 cdff21aa9a0f6aa5341e1c971146d1fc30febd1f 0               False   \n",
+       "2020-06-02 13:30:17.825000+00:00 10117bb7a0b195dc7b6aeaae78be69c10fa7d620 0               False   \n",
+       "                                                                          1               False   \n",
+       "                                 254d7d285416df46733e9541e4da21fc498d3502 0               False   \n",
+       "                                 4b6af7167d38d0751614ad390908dc4a8e0ef652 0               False   \n",
+       "\n",
+       "                                                                                       is_source  \\\n",
+       "                                 sha1                                     lic_det_num              \n",
+       "2019-04-17 14:19:10.672000+00:00 c31f1358e9e15586333a3a91298e770a9d360867 0                False   \n",
+       "                                 e5dad7813f1edf787936eedfa92c421bf28080c3 0                False   \n",
+       "2020-05-26 21:20:17.862000+00:00 15ecee2af9d79cc7c86d42b31b8778faf61e7e35 0                False   \n",
+       "                                 1c3a8a412cca20678559fce34b46686c39a835c0 0                False   \n",
+       "                                                                          1                False   \n",
+       "                                                                          2                False   \n",
+       "                                 3be892ba5a4cdc550ac746e257e8e944e79561de 0                False   \n",
+       "                                 3d5143b5fffba7880c3c2d10d73ae39740dbdd2c 0                 True   \n",
+       "                                 4828905332706cdfebe3dfe9f699bb6616abfd76 0                 True   \n",
+       "                                 7e75216e98490df3995164be00d5d6d4ae8d63cf 0                 True   \n",
+       "                                 9d5dc47d7b122dbfb7005e627a352ca001dddb73 0                 True   \n",
+       "                                 a5fddef68a032cd03b957cca5076c2244480a34b 0                 True   \n",
+       "                                 a6d104bee2f3a7610bb10ad379bfb6b0d3466f89 0                False   \n",
+       "                                 abcd264d3854a8b5cc987f265fb581b8c59ebe50 0                 True   \n",
+       "                                 da97ffed59276dce11663a7ddb468112811debeb 0                 True   \n",
+       "2019-10-10 21:19:38.969000+00:00 cdff21aa9a0f6aa5341e1c971146d1fc30febd1f 0                False   \n",
+       "2020-06-02 13:30:17.825000+00:00 10117bb7a0b195dc7b6aeaae78be69c10fa7d620 0                False   \n",
+       "                                                                          1                False   \n",
+       "                                 254d7d285416df46733e9541e4da21fc498d3502 0                False   \n",
+       "                                 4b6af7167d38d0751614ad390908dc4a8e0ef652 0                 True   \n",
+       "\n",
+       "                                                                                       ...  \\\n",
+       "                                 sha1                                     lic_det_num  ...   \n",
+       "2019-04-17 14:19:10.672000+00:00 c31f1358e9e15586333a3a91298e770a9d360867 0            ...   \n",
+       "                                 e5dad7813f1edf787936eedfa92c421bf28080c3 0            ...   \n",
+       "2020-05-26 21:20:17.862000+00:00 15ecee2af9d79cc7c86d42b31b8778faf61e7e35 0            ...   \n",
+       "                                 1c3a8a412cca20678559fce34b46686c39a835c0 0            ...   \n",
+       "                                                                          1            ...   \n",
+       "                                                                          2            ...   \n",
+       "                                 3be892ba5a4cdc550ac746e257e8e944e79561de 0            ...   \n",
+       "                                 3d5143b5fffba7880c3c2d10d73ae39740dbdd2c 0            ...   \n",
+       "                                 4828905332706cdfebe3dfe9f699bb6616abfd76 0            ...   \n",
+       "                                 7e75216e98490df3995164be00d5d6d4ae8d63cf 0            ...   \n",
+       "                                 9d5dc47d7b122dbfb7005e627a352ca001dddb73 0            ...   \n",
+       "                                 a5fddef68a032cd03b957cca5076c2244480a34b 0            ...   \n",
+       "                                 a6d104bee2f3a7610bb10ad379bfb6b0d3466f89 0            ...   \n",
+       "                                 abcd264d3854a8b5cc987f265fb581b8c59ebe50 0            ...   \n",
+       "                                 da97ffed59276dce11663a7ddb468112811debeb 0            ...   \n",
+       "2019-10-10 21:19:38.969000+00:00 cdff21aa9a0f6aa5341e1c971146d1fc30febd1f 0            ...   \n",
+       "2020-06-02 13:30:17.825000+00:00 10117bb7a0b195dc7b6aeaae78be69c10fa7d620 0            ...   \n",
+       "                                                                          1            ...   \n",
+       "                                 254d7d285416df46733e9541e4da21fc498d3502 0            ...   \n",
+       "                                 4b6af7167d38d0751614ad390908dc4a8e0ef652 0            ...   \n",
+       "\n",
+       "                                                                                                  identifier  \\\n",
+       "                                 sha1                                     lic_det_num                          \n",
+       "2019-04-17 14:19:10.672000+00:00 c31f1358e9e15586333a3a91298e770a9d360867 0                     mit_160.RULE   \n",
+       "                                 e5dad7813f1edf787936eedfa92c421bf28080c3 0                      mit_34.RULE   \n",
+       "2020-05-26 21:20:17.862000+00:00 15ecee2af9d79cc7c86d42b31b8778faf61e7e35 0                      mit_77.RULE   \n",
+       "                                 1c3a8a412cca20678559fce34b46686c39a835c0 0                      mit_34.RULE   \n",
+       "                                                                          1                      mit_77.RULE   \n",
+       "                                                                          2            pypi_mit_license.RULE   \n",
+       "                                 3be892ba5a4cdc550ac746e257e8e944e79561de 0                     mit_160.RULE   \n",
+       "                                 3d5143b5fffba7880c3c2d10d73ae39740dbdd2c 0            public-domain_45.RULE   \n",
+       "                                 4828905332706cdfebe3dfe9f699bb6616abfd76 0            public-domain_45.RULE   \n",
+       "                                 7e75216e98490df3995164be00d5d6d4ae8d63cf 0            pypi_mit_license.RULE   \n",
+       "                                 9d5dc47d7b122dbfb7005e627a352ca001dddb73 0                     mit_160.RULE   \n",
+       "                                 a5fddef68a032cd03b957cca5076c2244480a34b 0            public-domain_15.RULE   \n",
+       "                                 a6d104bee2f3a7610bb10ad379bfb6b0d3466f89 0                      mit_34.RULE   \n",
+       "                                 abcd264d3854a8b5cc987f265fb581b8c59ebe50 0            public-domain_45.RULE   \n",
+       "                                 da97ffed59276dce11663a7ddb468112811debeb 0                     mit_160.RULE   \n",
+       "2019-10-10 21:19:38.969000+00:00 cdff21aa9a0f6aa5341e1c971146d1fc30febd1f 0                      mit_34.RULE   \n",
+       "2020-06-02 13:30:17.825000+00:00 10117bb7a0b195dc7b6aeaae78be69c10fa7d620 0                  gpl-2.0_23.RULE   \n",
+       "                                                                          1            gpl-2.0-plus_310.RULE   \n",
+       "                                 254d7d285416df46733e9541e4da21fc498d3502 0                      mit_34.RULE   \n",
+       "                                 4b6af7167d38d0751614ad390908dc4a8e0ef652 0                 gpl-2.0_550.RULE   \n",
+       "\n",
+       "                                                                                      is_license_text_lic  \\\n",
+       "                                 sha1                                     lic_det_num                       \n",
+       "2019-04-17 14:19:10.672000+00:00 c31f1358e9e15586333a3a91298e770a9d360867 0                          True   \n",
+       "                                 e5dad7813f1edf787936eedfa92c421bf28080c3 0                         False   \n",
+       "2020-05-26 21:20:17.862000+00:00 15ecee2af9d79cc7c86d42b31b8778faf61e7e35 0                         False   \n",
+       "                                 1c3a8a412cca20678559fce34b46686c39a835c0 0                         False   \n",
+       "                                                                          1                         False   \n",
+       "                                                                          2                         False   \n",
+       "                                 3be892ba5a4cdc550ac746e257e8e944e79561de 0                          True   \n",
+       "                                 3d5143b5fffba7880c3c2d10d73ae39740dbdd2c 0                          True   \n",
+       "                                 4828905332706cdfebe3dfe9f699bb6616abfd76 0                          True   \n",
+       "                                 7e75216e98490df3995164be00d5d6d4ae8d63cf 0                         False   \n",
+       "                                 9d5dc47d7b122dbfb7005e627a352ca001dddb73 0                          True   \n",
+       "                                 a5fddef68a032cd03b957cca5076c2244480a34b 0                          True   \n",
+       "                                 a6d104bee2f3a7610bb10ad379bfb6b0d3466f89 0                         False   \n",
+       "                                 abcd264d3854a8b5cc987f265fb581b8c59ebe50 0                          True   \n",
+       "                                 da97ffed59276dce11663a7ddb468112811debeb 0                          True   \n",
+       "2019-10-10 21:19:38.969000+00:00 cdff21aa9a0f6aa5341e1c971146d1fc30febd1f 0                         False   \n",
+       "2020-06-02 13:30:17.825000+00:00 10117bb7a0b195dc7b6aeaae78be69c10fa7d620 0                         False   \n",
+       "                                                                          1                         False   \n",
+       "                                 254d7d285416df46733e9541e4da21fc498d3502 0                         False   \n",
+       "                                 4b6af7167d38d0751614ad390908dc4a8e0ef652 0                         False   \n",
+       "\n",
+       "                                                                                       is_license_notice  \\\n",
+       "                                 sha1                                     lic_det_num                      \n",
+       "2019-04-17 14:19:10.672000+00:00 c31f1358e9e15586333a3a91298e770a9d360867 0                        False   \n",
+       "                                 e5dad7813f1edf787936eedfa92c421bf28080c3 0                        False   \n",
+       "2020-05-26 21:20:17.862000+00:00 15ecee2af9d79cc7c86d42b31b8778faf61e7e35 0                        False   \n",
+       "                                 1c3a8a412cca20678559fce34b46686c39a835c0 0                        False   \n",
+       "                                                                          1                        False   \n",
+       "                                                                          2                        False   \n",
+       "                                 3be892ba5a4cdc550ac746e257e8e944e79561de 0                        False   \n",
+       "                                 3d5143b5fffba7880c3c2d10d73ae39740dbdd2c 0                        False   \n",
+       "                                 4828905332706cdfebe3dfe9f699bb6616abfd76 0                        False   \n",
+       "                                 7e75216e98490df3995164be00d5d6d4ae8d63cf 0                        False   \n",
+       "                                 9d5dc47d7b122dbfb7005e627a352ca001dddb73 0                        False   \n",
+       "                                 a5fddef68a032cd03b957cca5076c2244480a34b 0                        False   \n",
+       "                                 a6d104bee2f3a7610bb10ad379bfb6b0d3466f89 0                        False   \n",
+       "                                 abcd264d3854a8b5cc987f265fb581b8c59ebe50 0                        False   \n",
+       "                                 da97ffed59276dce11663a7ddb468112811debeb 0                        False   \n",
+       "2019-10-10 21:19:38.969000+00:00 cdff21aa9a0f6aa5341e1c971146d1fc30febd1f 0                        False   \n",
+       "2020-06-02 13:30:17.825000+00:00 10117bb7a0b195dc7b6aeaae78be69c10fa7d620 0                        False   \n",
+       "                                                                          1                        False   \n",
+       "                                 254d7d285416df46733e9541e4da21fc498d3502 0                        False   \n",
+       "                                 4b6af7167d38d0751614ad390908dc4a8e0ef652 0                        False   \n",
+       "\n",
+       "                                                                                       is_license_reference  \\\n",
+       "                                 sha1                                     lic_det_num                         \n",
+       "2019-04-17 14:19:10.672000+00:00 c31f1358e9e15586333a3a91298e770a9d360867 0                           False   \n",
+       "                                 e5dad7813f1edf787936eedfa92c421bf28080c3 0                           False   \n",
+       "2020-05-26 21:20:17.862000+00:00 15ecee2af9d79cc7c86d42b31b8778faf61e7e35 0                            True   \n",
+       "                                 1c3a8a412cca20678559fce34b46686c39a835c0 0                           False   \n",
+       "                                                                          1                            True   \n",
+       "                                                                          2                           False   \n",
+       "                                 3be892ba5a4cdc550ac746e257e8e944e79561de 0                           False   \n",
+       "                                 3d5143b5fffba7880c3c2d10d73ae39740dbdd2c 0                           False   \n",
+       "                                 4828905332706cdfebe3dfe9f699bb6616abfd76 0                           False   \n",
+       "                                 7e75216e98490df3995164be00d5d6d4ae8d63cf 0                           False   \n",
+       "                                 9d5dc47d7b122dbfb7005e627a352ca001dddb73 0                           False   \n",
+       "                                 a5fddef68a032cd03b957cca5076c2244480a34b 0                           False   \n",
+       "                                 a6d104bee2f3a7610bb10ad379bfb6b0d3466f89 0                           False   \n",
+       "                                 abcd264d3854a8b5cc987f265fb581b8c59ebe50 0                           False   \n",
+       "                                 da97ffed59276dce11663a7ddb468112811debeb 0                           False   \n",
+       "2019-10-10 21:19:38.969000+00:00 cdff21aa9a0f6aa5341e1c971146d1fc30febd1f 0                           False   \n",
+       "2020-06-02 13:30:17.825000+00:00 10117bb7a0b195dc7b6aeaae78be69c10fa7d620 0                           False   \n",
+       "                                                                          1                            True   \n",
+       "                                 254d7d285416df46733e9541e4da21fc498d3502 0                           False   \n",
+       "                                 4b6af7167d38d0751614ad390908dc4a8e0ef652 0                           False   \n",
+       "\n",
+       "                                                                                       is_license_tag  \\\n",
+       "                                 sha1                                     lic_det_num                   \n",
+       "2019-04-17 14:19:10.672000+00:00 c31f1358e9e15586333a3a91298e770a9d360867 0                     False   \n",
+       "                                 e5dad7813f1edf787936eedfa92c421bf28080c3 0                      True   \n",
+       "2020-05-26 21:20:17.862000+00:00 15ecee2af9d79cc7c86d42b31b8778faf61e7e35 0                     False   \n",
+       "                                 1c3a8a412cca20678559fce34b46686c39a835c0 0                      True   \n",
+       "                                                                          1                     False   \n",
+       "                                                                          2                      True   \n",
+       "                                 3be892ba5a4cdc550ac746e257e8e944e79561de 0                     False   \n",
+       "                                 3d5143b5fffba7880c3c2d10d73ae39740dbdd2c 0                     False   \n",
+       "                                 4828905332706cdfebe3dfe9f699bb6616abfd76 0                     False   \n",
+       "                                 7e75216e98490df3995164be00d5d6d4ae8d63cf 0                      True   \n",
+       "                                 9d5dc47d7b122dbfb7005e627a352ca001dddb73 0                     False   \n",
+       "                                 a5fddef68a032cd03b957cca5076c2244480a34b 0                     False   \n",
+       "                                 a6d104bee2f3a7610bb10ad379bfb6b0d3466f89 0                      True   \n",
+       "                                 abcd264d3854a8b5cc987f265fb581b8c59ebe50 0                     False   \n",
+       "                                 da97ffed59276dce11663a7ddb468112811debeb 0                     False   \n",
+       "2019-10-10 21:19:38.969000+00:00 cdff21aa9a0f6aa5341e1c971146d1fc30febd1f 0                      True   \n",
+       "2020-06-02 13:30:17.825000+00:00 10117bb7a0b195dc7b6aeaae78be69c10fa7d620 0                      True   \n",
+       "                                                                          1                     False   \n",
+       "                                 254d7d285416df46733e9541e4da21fc498d3502 0                      True   \n",
+       "                                 4b6af7167d38d0751614ad390908dc4a8e0ef652 0                      True   \n",
+       "\n",
+       "                                                                                       matcher  \\\n",
+       "                                 sha1                                     lic_det_num            \n",
+       "2019-04-17 14:19:10.672000+00:00 c31f1358e9e15586333a3a91298e770a9d360867 0              3-seq   \n",
+       "                                 e5dad7813f1edf787936eedfa92c421bf28080c3 0              2-aho   \n",
+       "2020-05-26 21:20:17.862000+00:00 15ecee2af9d79cc7c86d42b31b8778faf61e7e35 0              2-aho   \n",
+       "                                 1c3a8a412cca20678559fce34b46686c39a835c0 0              2-aho   \n",
+       "                                                                          1              2-aho   \n",
+       "                                                                          2              2-aho   \n",
+       "                                 3be892ba5a4cdc550ac746e257e8e944e79561de 0              3-seq   \n",
+       "                                 3d5143b5fffba7880c3c2d10d73ae39740dbdd2c 0              2-aho   \n",
+       "                                 4828905332706cdfebe3dfe9f699bb6616abfd76 0              2-aho   \n",
+       "                                 7e75216e98490df3995164be00d5d6d4ae8d63cf 0              2-aho   \n",
+       "                                 9d5dc47d7b122dbfb7005e627a352ca001dddb73 0              3-seq   \n",
+       "                                 a5fddef68a032cd03b957cca5076c2244480a34b 0              2-aho   \n",
+       "                                 a6d104bee2f3a7610bb10ad379bfb6b0d3466f89 0              2-aho   \n",
+       "                                 abcd264d3854a8b5cc987f265fb581b8c59ebe50 0              2-aho   \n",
+       "                                 da97ffed59276dce11663a7ddb468112811debeb 0              3-seq   \n",
+       "2019-10-10 21:19:38.969000+00:00 cdff21aa9a0f6aa5341e1c971146d1fc30febd1f 0              2-aho   \n",
+       "2020-06-02 13:30:17.825000+00:00 10117bb7a0b195dc7b6aeaae78be69c10fa7d620 0              2-aho   \n",
+       "                                                                          1              3-seq   \n",
+       "                                 254d7d285416df46733e9541e4da21fc498d3502 0              2-aho   \n",
+       "                                 4b6af7167d38d0751614ad390908dc4a8e0ef652 0              2-aho   \n",
+       "\n",
+       "                                                                                       rule_length  \\\n",
+       "                                 sha1                                     lic_det_num                \n",
+       "2019-04-17 14:19:10.672000+00:00 c31f1358e9e15586333a3a91298e770a9d360867 0                    167   \n",
+       "                                 e5dad7813f1edf787936eedfa92c421bf28080c3 0                      2   \n",
+       "2020-05-26 21:20:17.862000+00:00 15ecee2af9d79cc7c86d42b31b8778faf61e7e35 0                      4   \n",
+       "                                 1c3a8a412cca20678559fce34b46686c39a835c0 0                      2   \n",
+       "                                                                          1                      4   \n",
+       "                                                                          2                      5   \n",
+       "                                 3be892ba5a4cdc550ac746e257e8e944e79561de 0                    167   \n",
+       "                                 3d5143b5fffba7880c3c2d10d73ae39740dbdd2c 0                      5   \n",
+       "                                 4828905332706cdfebe3dfe9f699bb6616abfd76 0                      5   \n",
+       "                                 7e75216e98490df3995164be00d5d6d4ae8d63cf 0                      5   \n",
+       "                                 9d5dc47d7b122dbfb7005e627a352ca001dddb73 0                    167   \n",
+       "                                 a5fddef68a032cd03b957cca5076c2244480a34b 0                      5   \n",
+       "                                 a6d104bee2f3a7610bb10ad379bfb6b0d3466f89 0                      2   \n",
+       "                                 abcd264d3854a8b5cc987f265fb581b8c59ebe50 0                      5   \n",
+       "                                 da97ffed59276dce11663a7ddb468112811debeb 0                    167   \n",
+       "2019-10-10 21:19:38.969000+00:00 cdff21aa9a0f6aa5341e1c971146d1fc30febd1f 0                      2   \n",
+       "2020-06-02 13:30:17.825000+00:00 10117bb7a0b195dc7b6aeaae78be69c10fa7d620 0                      2   \n",
+       "                                                                          1                     12   \n",
+       "                                 254d7d285416df46733e9541e4da21fc498d3502 0                      2   \n",
+       "                                 4b6af7167d38d0751614ad390908dc4a8e0ef652 0                      4   \n",
+       "\n",
+       "                                                                                       matched_length  \\\n",
+       "                                 sha1                                     lic_det_num                   \n",
+       "2019-04-17 14:19:10.672000+00:00 c31f1358e9e15586333a3a91298e770a9d360867 0                       166   \n",
+       "                                 e5dad7813f1edf787936eedfa92c421bf28080c3 0                         2   \n",
+       "2020-05-26 21:20:17.862000+00:00 15ecee2af9d79cc7c86d42b31b8778faf61e7e35 0                         4   \n",
+       "                                 1c3a8a412cca20678559fce34b46686c39a835c0 0                         2   \n",
+       "                                                                          1                         4   \n",
+       "                                                                          2                         5   \n",
+       "                                 3be892ba5a4cdc550ac746e257e8e944e79561de 0                       166   \n",
+       "                                 3d5143b5fffba7880c3c2d10d73ae39740dbdd2c 0                         5   \n",
+       "                                 4828905332706cdfebe3dfe9f699bb6616abfd76 0                         5   \n",
+       "                                 7e75216e98490df3995164be00d5d6d4ae8d63cf 0                         5   \n",
+       "                                 9d5dc47d7b122dbfb7005e627a352ca001dddb73 0                       166   \n",
+       "                                 a5fddef68a032cd03b957cca5076c2244480a34b 0                         5   \n",
+       "                                 a6d104bee2f3a7610bb10ad379bfb6b0d3466f89 0                         2   \n",
+       "                                 abcd264d3854a8b5cc987f265fb581b8c59ebe50 0                         5   \n",
+       "                                 da97ffed59276dce11663a7ddb468112811debeb 0                       166   \n",
+       "2019-10-10 21:19:38.969000+00:00 cdff21aa9a0f6aa5341e1c971146d1fc30febd1f 0                         2   \n",
+       "2020-06-02 13:30:17.825000+00:00 10117bb7a0b195dc7b6aeaae78be69c10fa7d620 0                         2   \n",
+       "                                                                          1                        11   \n",
+       "                                 254d7d285416df46733e9541e4da21fc498d3502 0                         2   \n",
+       "                                 4b6af7167d38d0751614ad390908dc4a8e0ef652 0                         4   \n",
+       "\n",
+       "                                                                                       match_coverage  \\\n",
+       "                                 sha1                                     lic_det_num                   \n",
+       "2019-04-17 14:19:10.672000+00:00 c31f1358e9e15586333a3a91298e770a9d360867 0                     99.40   \n",
+       "                                 e5dad7813f1edf787936eedfa92c421bf28080c3 0                    100.00   \n",
+       "2020-05-26 21:20:17.862000+00:00 15ecee2af9d79cc7c86d42b31b8778faf61e7e35 0                    100.00   \n",
+       "                                 1c3a8a412cca20678559fce34b46686c39a835c0 0                    100.00   \n",
+       "                                                                          1                    100.00   \n",
+       "                                                                          2                    100.00   \n",
+       "                                 3be892ba5a4cdc550ac746e257e8e944e79561de 0                     99.40   \n",
+       "                                 3d5143b5fffba7880c3c2d10d73ae39740dbdd2c 0                    100.00   \n",
+       "                                 4828905332706cdfebe3dfe9f699bb6616abfd76 0                    100.00   \n",
+       "                                 7e75216e98490df3995164be00d5d6d4ae8d63cf 0                    100.00   \n",
+       "                                 9d5dc47d7b122dbfb7005e627a352ca001dddb73 0                     99.40   \n",
+       "                                 a5fddef68a032cd03b957cca5076c2244480a34b 0                    100.00   \n",
+       "                                 a6d104bee2f3a7610bb10ad379bfb6b0d3466f89 0                    100.00   \n",
+       "                                 abcd264d3854a8b5cc987f265fb581b8c59ebe50 0                    100.00   \n",
+       "                                 da97ffed59276dce11663a7ddb468112811debeb 0                     99.40   \n",
+       "2019-10-10 21:19:38.969000+00:00 cdff21aa9a0f6aa5341e1c971146d1fc30febd1f 0                    100.00   \n",
+       "2020-06-02 13:30:17.825000+00:00 10117bb7a0b195dc7b6aeaae78be69c10fa7d620 0                    100.00   \n",
+       "                                                                          1                     91.67   \n",
+       "                                 254d7d285416df46733e9541e4da21fc498d3502 0                    100.00   \n",
+       "                                 4b6af7167d38d0751614ad390908dc4a8e0ef652 0                    100.00   \n",
+       "\n",
+       "                                                                                       rule_relevance  \n",
+       "                                 sha1                                     lic_det_num                  \n",
+       "2019-04-17 14:19:10.672000+00:00 c31f1358e9e15586333a3a91298e770a9d360867 0                       100  \n",
+       "                                 e5dad7813f1edf787936eedfa92c421bf28080c3 0                        99  \n",
+       "2020-05-26 21:20:17.862000+00:00 15ecee2af9d79cc7c86d42b31b8778faf61e7e35 0                        22  \n",
+       "                                 1c3a8a412cca20678559fce34b46686c39a835c0 0                        99  \n",
+       "                                                                          1                        22  \n",
+       "                                                                          2                        27  \n",
+       "                                 3be892ba5a4cdc550ac746e257e8e944e79561de 0                       100  \n",
+       "                                 3d5143b5fffba7880c3c2d10d73ae39740dbdd2c 0                        27  \n",
+       "                                 4828905332706cdfebe3dfe9f699bb6616abfd76 0                        27  \n",
+       "                                 7e75216e98490df3995164be00d5d6d4ae8d63cf 0                        27  \n",
+       "                                 9d5dc47d7b122dbfb7005e627a352ca001dddb73 0                       100  \n",
+       "                                 a5fddef68a032cd03b957cca5076c2244480a34b 0                       100  \n",
+       "                                 a6d104bee2f3a7610bb10ad379bfb6b0d3466f89 0                        99  \n",
+       "                                 abcd264d3854a8b5cc987f265fb581b8c59ebe50 0                        27  \n",
+       "                                 da97ffed59276dce11663a7ddb468112811debeb 0                       100  \n",
+       "2019-10-10 21:19:38.969000+00:00 cdff21aa9a0f6aa5341e1c971146d1fc30febd1f 0                        99  \n",
+       "2020-06-02 13:30:17.825000+00:00 10117bb7a0b195dc7b6aeaae78be69c10fa7d620 0                       100  \n",
+       "                                                                          1                        66  \n",
+       "                                 254d7d285416df46733e9541e4da21fc498d3502 0                        99  \n",
+       "                                 4b6af7167d38d0751614ad390908dc4a8e0ef652 0                       100  \n",
+       "\n",
+       "[20 rows x 37 columns]"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "main_dataframe.head(20)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/src/notebooks/postgres.ipynb b/src/notebooks/postgres.ipynb
new file mode 100644
index 0000000..ac385a4
--- /dev/null
+++ b/src/notebooks/postgres.ipynb
@@ -0,0 +1,140 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# `postgres.py`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "sys.path.append('/home/ayan/Desktop/nexB/gsoc20/scancode-results-analyzer/src')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Import Class `PostgresFetch` and initialize Object"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from results_analyze.postgres import PostgresFetch\n",
+    "post_ayan = PostgresFetch()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Formats Query from Postgres Database `PostgresFetch.format_query`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false,
+    "jupyter": {
+     "outputs_hidden": false
+    },
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\"SELECT path, content FROM clearcode_cditem WHERE path like '%/scancode/%'OFFSET 0 ROWS FETCH FIRST 10 ROW ONLY;\""
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "post_ayan.format_query(num_rows=10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Fetch Data from Postgres Database `PostgresFetch.fetch_data`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[('git/github/zzarcon/video-snapshot/revision/b56386f225a2d082b1e56a0f24cfda595798c654/tool/scancode/3.2.2.json',\n",
+       "  <memory at 0x7f2df4766588>),\n",
+       " ('pypi/pypi/-/ccxt/revision/1.28.76/tool/scancode/3.2.2.json',\n",
+       "  <memory at 0x7f2df4766648>),\n",
+       " ('composer/packagist/motor-cms/motor-core/revision/0.9.1/tool/scancode/3.2.2.json',\n",
+       "  <memory at 0x7f2df4766708>),\n",
+       " ('composer/packagist/lucatume/wp-browser/revision/2.5.7/tool/scancode/3.2.2.json',\n",
+       "  <memory at 0x7f2df47667c8>),\n",
+       " ('npm/npmjs/-/aws-sdk/revision/2.687.0/tool/scancode/3.2.2.json',\n",
+       "  <memory at 0x7f2df4766888>),\n",
+       " ('npm/npmjs/@types/babel__core/revision/7.1.8/tool/scancode/3.2.2.json',\n",
+       "  <memory at 0x7f2df4766948>),\n",
+       " ('composer/packagist/topshelfcraft/wordsmith/revision/3.1.0/tool/scancode/3.2.2.json',\n",
+       "  <memory at 0x7f2df4766a08>),\n",
+       " ('pypi/pypi/-/youtube_dl/revision/2014.01.22.4/tool/scancode/3.2.2.json',\n",
+       "  <memory at 0x7f2df4766ac8>),\n",
+       " ('composer/packagist/qingbing/php-file-cache/revision/1.0.1/tool/scancode/3.2.2.json',\n",
+       "  <memory at 0x7f2df4766b88>),\n",
+       " ('git/github/fnando/browser/revision/9ada0e23745b82eef15035fc86fe560f826e0018/tool/scancode/3.2.2.json',\n",
+       "  <memory at 0x7f2df4766c48>)]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "post_ayan.fetch_data(10)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/src/results_analyze/data/credentials.json b/src/results_analyze/data/credentials.json
new file mode 100644
index 0000000..80663a4
--- /dev/null
+++ b/src/results_analyze/data/credentials.json
@@ -0,0 +1 @@
+{"user": "clearcode", "password": "REPLACE_WITH_PASSWORD", "host": "127.0.0.1", "port": "5432", "database": "clearcode"}
\ No newline at end of file
diff --git a/src/results_analyze/load_results_file.py b/src/results_analyze/load_results_file.py
new file mode 100644
index 0000000..4227615
--- /dev/null
+++ b/src/results_analyze/load_results_file.py
@@ -0,0 +1,146 @@
+#
+# Copyright (c) nexB Inc. and others. All rights reserved.
+# http://nexb.com and https://github.com/nexB/scancode-toolkit/
+# The ScanCode software is licensed under the Apache License version 2.0.
+# Data generated with ScanCode require an acknowledgment.
+# ScanCode is a trademark of nexB Inc.
+#
+# You may not use this software except in compliance with the License.
+# You may obtain a copy of the License at: http://apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software distributed
+# under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
+# CONDITIONS OF ANY KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations under the License.
+#
+# When you publish or redistribute any data created with ScanCode or any ScanCode
+# derivative work, you must accompany this data with the following acknowledgment:
+#
+#  Generated with ScanCode and provided on an "AS IS" BASIS, WITHOUT WARRANTIES
+#  OR CONDITIONS OF ANY KIND, either express or implied. No content created from
+#  ScanCode should be considered or used as legal advice. Consult an Attorney
+#  for any legal advice.
+#  ScanCode is a free software code scanning tool from nexB Inc. and others.
+#  Visit https://github.com/nexB/scancode-toolkit/ for support and download.
+
+
+import numpy as np
+import pandas as pd
+
+
+class ResultsDataFrameFile:
+    def __init__(self):
+        # Which columns to drop from a File Level Dataframe.
+        self.drop_columns_list_file_lev = ['type', 'name', 'base_name', 'extension', 'date', 'md5',
+                                           'license_expressions', 'holders', 'copyrights', 'authors', 'packages',
+                                           'emails', 'urls', 'files_count', 'dirs_count', 'size_count', 'scan_errors']
+        # Which columns to drop from a License Level Dataframe.
+        self.drop_columns_list_lic_lev = ['name', 'short_name', 'owner', 'homepage_url', 'text_url', 'reference_url',
+                                          'spdx_license_key', 'spdx_url', 'license_expression', 'matched_rule',
+                                          'licenses']
+
+    @staticmethod
+    def dict_to_rows_matched_rule_dataframes_apply(dataframe):
+        """
+        Makes Dicts keys inside dict 'matched_rule' -> Columns of License level DataFrame.
+
+        :param dataframe: pd.DataFrame
+        """
+        new_df = pd.DataFrame(list(dataframe['matched_rule']))
+
+        # Merge By Index, which basically Appends Column-Wise
+        dataframe = dataframe.join(new_df)
+
+        return dataframe
+
+    def modify_lic_level_dataframe(self, dataframe_lic):
+        """
+        Modifies License level DataFrame, from 'matched_rule' dicts, bring information to columns.
+        Maps Rule Names and other strings to integer values to compress.
+
+        :param dataframe_lic: pd.DataFrame
+        :return dataframe_lic: pd.DataFrame
+        """
+        # From dict 'matched_rule' expand keys to DataFrame Columns
+        dataframe_lic_rule = self.dict_to_rows_matched_rule_dataframes_apply(dataframe_lic)
+
+        # Drops Unnecessary Columns
+        dataframe_lic_rule.drop(columns=self.drop_columns_list_lic_lev, inplace=True)
+
+        # ToDo: Map Strings to Int Values
+
+        return dataframe_lic_rule
+
+    def create_lic_level_dataframe(self, file_level_dataframe):
+        """
+        Takes a File Level DataFrame, creates license level dataframes, modifies and cleans them up and
+        appends columns to file level dataframes. Here, already existing file level info is also present at each
+        license level rows.
+
+        :param file_level_dataframe: pd.DataFrame
+        :returns merged_df: pd.DataFrame
+        """
+        # For each file, add license level dict-keys to new columns, and multiple licenses per file into new rows
+        # Introduces new column 'level_1'(renamed to 'lic_det_num'), which is the primary key for
+        # each license detection inside one file.
+        lic_level_dataframe = file_level_dataframe.groupby('sha1').licenses.apply(
+            lambda x: pd.DataFrame(x.values[0])).reset_index()
+        lic_level_dataframe.rename(columns={'level_1': 'lic_det_num'}, inplace=True)
+
+        # Modifies license level information
+        lic_level_dataframe = self.modify_lic_level_dataframe(lic_level_dataframe)
+
+        # makes sha1 column as the file level Index [Primary Key].
+        lic_level_dataframe.set_index('sha1', inplace=True)
+
+        merged_df = file_level_dataframe.join(lic_level_dataframe, lsuffix='_file', rsuffix='_lic')
+        merged_df.reset_index(inplace=True)
+
+        return merged_df
+
+    def modify_file_level_dataframe(self, dataframe_files):
+        """
+        Takes a File Level DataFrame, drops unnecessary columns, drops all directory rows, drops same files,
+        drop files with no license detections, and makes sha1 column as the file level Index [Primary Key].
+
+        :param dataframe_files: pd.DataFrame
+            File Level DataFrames
+        """
+        # Drops Unnecessary Columns
+        dataframe_files.drop(columns=self.drop_columns_list_file_lev, inplace=True)
+
+        # Drops all rows with file_type as directories, as they have `NaN` as their `sha1` values
+        dataframe_files.dropna(subset=['sha1'], inplace=True)
+
+        # Add a column number of license detections per file, and drop files with no license detections
+        dataframe_files['license_detections_no'] = dataframe_files.licenses.apply(lambda x: np.shape(x)[0])
+        dataframe_files.drop(dataframe_files[~ (dataframe_files['license_detections_no'] > 0)].index, inplace=True)
+
+        # Drops files that have the same sha1 hash, i.e. essentially similar files
+        dataframe_files.drop_duplicates(subset='sha1', keep="last", inplace=True)
+
+        # Makes SHA1 column the index (Slows down calculations)
+        dataframe_files.set_index('sha1', inplace=True)
+
+        return
+
+    def create_file_level_dataframe(self, package_files_list):
+        """
+        Creates a File and License Level DataFrame
+
+        :param package_files_list: list of file level dicts
+        :returns file_and_lic_level_dataframe: pd.DataFrame
+            Has File and License level information organized via pd.MultiIndex.
+        """
+        # Initialize the file package level list into a DataFrame (Row - Files, Columns - Dict keys inside Files)
+        file_level_dataframe = pd.DataFrame(package_files_list)
+
+        # Clean Up and Modify the File Level DataFrame
+        self.modify_file_level_dataframe(file_level_dataframe)
+
+        # From column 'licenses', which is a list of dicts, create License Level DataFrames
+        file_and_lic_level_dataframe = self.create_lic_level_dataframe(file_level_dataframe)
+
+        # Sets 'sha1' and 'lic_det_num' columns as the Indexes (Primary Key Tuple)
+        file_and_lic_level_dataframe.set_index(['sha1', 'lic_det_num'], inplace=True)
+
+        return file_and_lic_level_dataframe
diff --git a/src/results_analyze/load_results_package.py b/src/results_analyze/load_results_package.py
new file mode 100644
index 0000000..f0acfba
--- /dev/null
+++ b/src/results_analyze/load_results_package.py
@@ -0,0 +1,303 @@
+#
+# Copyright (c) nexB Inc. and others. All rights reserved.
+# http://nexb.com and https://github.com/nexB/scancode-toolkit/
+# The ScanCode software is licensed under the Apache License version 2.0.
+# Data generated with ScanCode require an acknowledgment.
+# ScanCode is a trademark of nexB Inc.
+#
+# You may not use this software except in compliance with the License.
+# You may obtain a copy of the License at: http://apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software distributed
+# under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
+# CONDITIONS OF ANY KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations under the License.
+#
+# When you publish or redistribute any data created with ScanCode or any ScanCode
+# derivative work, you must accompany this data with the following acknowledgment:
+#
+#  Generated with ScanCode and provided on an "AS IS" BASIS, WITHOUT WARRANTIES
+#  OR CONDITIONS OF ANY KIND, either express or implied. No content created from
+#  ScanCode should be considered or used as legal advice. Consult an Attorney
+#  for any legal advice.
+#  ScanCode is a free software code scanning tool from nexB Inc. and others.
+#  Visit https://github.com/nexB/scancode-toolkit/ for support and download.
+
+import os
+
+import gzip
+import json
+import pandas as pd
+
+from results_analyze.postgres import PostgresFetch
+from results_analyze.load_results_file import ResultsDataFrameFile
+
+# How many rows of Database to Fetch at once
+# ToDo: Calculation Function based on memory usage stats and RAM/SWAP Available
+NUM_ROWS_TO_FETCH = 20
+
+# 'table' (A bit slower, On-Disk Search/Query Enabled) or 'fixed' (Fast, No On-Disk Search/Query)
+HDF5_STORE_FORMAT = 'table'
+
+
+class ResultsDataFramePackage:
+
+    def __init__(self):
+        """
+        Constructor for ResultsDataFramePackage, initialized PostgresFetch and ResultsDataFrameFile objects,
+        and data paths and filenames used.
+        """
+        self.postgres = PostgresFetch()
+        self.results_file = ResultsDataFrameFile()
+        self.metadata_filename = 'projects_metadata.h5'
+        self.hdf_dir = os.path.join(os.path.dirname(__file__), 'data/hdf5/')
+
+    @staticmethod
+    def get_hdf5_file_path(hdf_dir, filename):
+        """
+        Gets filepath.
+
+        :param hdf_dir : string
+        :param filename : string
+
+        :returns filepath : os.Path
+        """
+        file_path = os.path.join(hdf_dir, filename)
+        return file_path
+
+    # ToDo: Support Selective Query/Search
+    @staticmethod
+    def load_dataframe_from_hdf5(file_path, df_key):
+        """
+        Loads data from the hdf5 to a Pandas Dataframe.
+
+        :param file_path : string
+        :param df_key : string
+
+        :returns filepath : pd.DataFrame object containing the Data read from the hdf5 file.
+        """
+
+        dataframe = pd.read_hdf(path_or_buf=file_path, key=df_key)
+
+        return dataframe
+
+    @staticmethod
+    def store_dataframe_to_hdf5(dataframe, file_path, df_key, h5_format=HDF5_STORE_FORMAT, is_append=False):
+        """
+        Stores data from the a Pandas Dataframe to hdf5.
+
+        :param dataframe : pd.Dataframe
+            The DataFrame which has to be stored
+        :param file_path : string
+        :param df_key: string
+            Table name inside the h5 file for this dataframe.
+        :param h5_format : string
+            PyTables storage format
+        :param is_append : bool
+        """
+
+        if is_append:
+            # File has to exist
+            dataframe.to_hdf(path_or_buf=file_path, key=df_key, mode='r+', format=h5_format)
+        else:
+            dataframe.to_hdf(path_or_buf=file_path, key=df_key, mode='w', format=h5_format)
+
+    def append_metadata_dataframe(self, metadata_dataframe):
+        """
+        Stores data from the a Pandas Dataframe, containing metadata to hdf5. Creates file if file doesn't exist.
+
+        :param metadata_dataframe : pd.Dataframe
+            The metadata DataFrame which has to be appended
+        """
+
+        file_path = os.path.join(self.get_hdf5_file_path(self.hdf_dir, self.metadata_filename))
+
+        if not os.path.isfile(self.get_hdf5_file_path(self.hdf_dir, filename=self.metadata_filename)):
+            self.store_dataframe_to_hdf5(metadata_dataframe, file_path, df_key='metadata',
+                                         h5_format='Table', is_append=False)
+        else:
+            self.store_dataframe_to_hdf5(metadata_dataframe, file_path, df_key='metadata',
+                                         h5_format='Table', is_append=True)
+
+    @staticmethod
+    def decompress_dataframe(compressed_dataframe):
+        """
+        This function is applied to one column of a Dataframe containing memoryview objects, at once,
+        using the DataFrame.apply() method, to perform vectorized decompression. Returns a Pandas Series object
+         each row having the corresponding JSON dict.
+
+        :param compressed_dataframe : pd.Series
+            One column of a DataFrame, containing Compressed memoryview objects.
+
+        :returns decompressed_dataframe : pd.Series
+            One column of a DataFrame, containing JSON dicts of Scan Results.
+        """
+        string_json = gzip.decompress(compressed_dataframe).decode('utf-8')
+        decompressed_dataframe = json.loads(string_json)
+
+        return decompressed_dataframe
+
+    def convert_records_to_json(self, num_rows_to_fetch=NUM_ROWS_TO_FETCH):
+        """
+        Fetch scan_results from Postgres Database, Load into Pandas Dataframes, and Decompress into JSON dicts.
+
+        :param num_rows_to_fetch : int
+            Number of Rows to Fetch from the Postgres Database, which is essentially the number of packages scanned.
+
+        :returns dataframe_memoryview : pd.DataFrame
+            DataFrame containing two Columns 'path' and 'json_content'.
+        """
+        # Fetch A specified rows of Data From postgres Database, and load into a DataFrame
+        data_memoryview = self.postgres.fetch_data(num_rows_to_fetch)
+        dataframe_memoryview = pd.DataFrame(data_memoryview, columns=['path', 'memoryview'])
+
+        # Decompress entire `memoryview` column, add decompressed JSON dicts at `json_content`, then drop former.
+        dataframe_memoryview['json_content'] = dataframe_memoryview.memoryview.apply(self.decompress_dataframe)
+        dataframe_memoryview.drop(columns=['memoryview'], inplace=True)
+
+        return dataframe_memoryview
+
+    @staticmethod
+    def dict_to_rows_in_dataframes(dataframe, key_1, key_2):
+        """
+        This function is applied to one column of a Dataframe containing json dicts, at once,
+        using the DataFrame.apply() method, to perform vectorized data retrieval.
+
+        :param dataframe : pd.Series
+            One column of a DataFrame, containing json dicts.
+        :param key_1 : string
+        :param key_2 : string
+
+        :returns row_data : pd.Series
+            One column of a DataFrame, containing values/dicts/lists that were inside those JSON dicts.
+        """
+        row_data = dataframe[key_1][key_2]
+
+        return row_data
+
+    def dict_to_rows_in_dataframes_apply(self, dataframe, key_1, key_2):
+        """
+        This function is applied to one column of a Dataframe containing json dicts, at once, to perform
+        vectorized data retrieval. Then convert the column of dicts to a list of dicts, to create dataframes from them.
+        The DataFrames columns are those dict keys.
+
+        :param dataframe : pd.DataFrame
+            DataFrame, containing json dicts in a column.
+        :param key_1 : string
+        :param key_2 : string
+
+        :returns dataframe : pd.DataFrame
+            DataFrame, containing new columns for each dict keys, from the dict inside the JSON dict.
+        """
+        dataframe_dicts = dataframe.json_content.apply(self.dict_to_rows_in_dataframes, args=(key_1, key_2))
+        new_df = pd.DataFrame(list(dataframe_dicts))
+
+        # Merge By Index, which basically Appends Column-Wise
+        dataframe = dataframe.join(new_df)
+
+        return dataframe
+
+    def value_to_rows_in_dataframes_apply(self, dataframe, key_1, key_2, name_value):
+        """
+        This function is applied to one column of a Dataframe containing json dicts, at once, to perform
+        vectorized data retrieval. Then convert this row of values/lists to dataframes.
+        The DataFrames column name is the `name_value`.
+
+        :param dataframe : pd.DataFrame
+            One column of a DataFrame, containing json dicts.
+        :param key_1 : string
+        :param key_2 : string
+        :param name_value : string
+
+        :return dataframe : pd.DataFrame
+            DataFrame, containing a new column for the value/list, from inside the JSON dict.
+        """
+        dataframe_dicts = dataframe.json_content.apply(self.dict_to_rows_in_dataframes, args=(key_1, key_2))
+        new_df = pd.DataFrame({name_value: dataframe_dicts})
+
+        # Merge By Index, which basically Appends Column-Wise
+        dataframe = dataframe.join(new_df)
+
+        return dataframe
+
+    @staticmethod
+    def convert_string_to_datetime(dataframe, old_col, new_col):
+        """
+        This function takes a column of string datetime, and converts it into Pandas DatetimeIndex objects.
+
+        :param dataframe : pd.DatFrame
+        :param old_col : string : Name of Old Column
+        :param new_col : string : Name of New Column
+        """
+        # Add Pandas DateTime Column
+        dataframe[new_col] = pd.to_datetime(dataframe[old_col].tolist(), format='%Y-%m-%d')
+
+        # Drop String DateTime Column
+        dataframe.drop(columns=[old_col], inplace=True)
+
+    def modify_package_level_dataframe(self, metadata_dataframe):
+        """
+        This function is applied to one column of a Dataframe containing json dicts, at once, to perform
+        vectorized data retrieval. Then convert this row of values/lists to dataframes.
+        The DataFrames column name is the `name_value`.
+
+        :param metadata_dataframe : pd.DataFrame
+
+        :returns files_dataframe : pd.DataFrame
+            DataFrame, containing a two columns, which has the path_string in one, and has a list of dicts in each row
+            of the other column, which is list of file-level dicts.
+        :returns metadata_dataframe : pd.DataFrame
+            DataFrame, containing a new column for the value/list, from inside the JSON dict.
+        """
+        metadata_dataframe = self.dict_to_rows_in_dataframes_apply(metadata_dataframe, key_1='content',
+                                                                   key_2='license_clarity_score')
+        metadata_dataframe = self.value_to_rows_in_dataframes_apply(metadata_dataframe, key_1='_metadata',
+                                                                    key_2='processedAt', name_value='TimeProcess')
+        metadata_dataframe = self.value_to_rows_in_dataframes_apply(metadata_dataframe, key_1='content', key_2='files',
+                                                                    name_value='Files')
+        metadata_dataframe.drop(columns=['json_content'], inplace=True)
+
+        # Convert TimeProcess to TimeIndex
+        self.convert_string_to_datetime(metadata_dataframe, old_col='TimeProcess', new_col='TimeIndex')
+
+        files_dataframe = metadata_dataframe[['TimeIndex', 'Files']].copy(deep=True)
+        metadata_dataframe.drop(columns=['Files'], inplace=True)
+
+        return files_dataframe, metadata_dataframe
+
+    def create_package_level_dataframe(self):
+        """
+        Creates a Package Level DataFrame, with File/License Information Levels.
+
+        :returns main_dataframe : df.DataFrame object
+            Main Storage DataFrame
+            Has Project, File and License level information organized via pd.MultiIndex.
+        """
+        # Loads Dataframes
+        path_json_dataframe = self.convert_records_to_json()
+
+        # ToDo: Assert Scancode Options
+
+        # Converts information multiple levels inside dicts into columns
+        # Package Level Data, TimeStamp, 'license_clarity_score' values,'files' list -> `New Columns`.
+        files_dataframe, metadata_dataframe = self.modify_package_level_dataframe(path_json_dataframe)
+
+        # Append metadata level information to a MetaData File
+        self.append_metadata_dataframe(metadata_dataframe)
+
+        # Iterate through all rows, (i.e. package scans), and calls file level function for each
+        # Appends the File and License Level DataFrame returned to a List.
+        file_level_dataframes_list = []
+        for package_scan_result in files_dataframe.itertuples():
+            file_level_dataframe = self.results_file.create_file_level_dataframe(package_scan_result[2])
+            file_level_dataframes_list.append(file_level_dataframe)
+
+        # Creates File level keys, which are used to create package level keys in the MultiIndex
+        list_file_level_keys = list(files_dataframe['TimeIndex'])
+
+        # Concatenate File Level Dataframes from the list, and their corresponding keys
+        #  into One Package Level Dataframe, using MultiIndex. Rename Primary Key column names.
+        main_dataframe = pd.concat(file_level_dataframes_list,
+                                   keys=list_file_level_keys)
+        main_dataframe.index.names = ['pkg_scan_time', 'file_sha1', 'lic_det_num']
+
+        return main_dataframe
diff --git a/src/results_analyze/postgres.py b/src/results_analyze/postgres.py
new file mode 100644
index 0000000..cf1009d
--- /dev/null
+++ b/src/results_analyze/postgres.py
@@ -0,0 +1,135 @@
+#
+# Copyright (c) nexB Inc. and others. All rights reserved.
+# http://nexb.com and https://github.com/nexB/scancode-toolkit/
+# The ScanCode software is licensed under the Apache License version 2.0.
+# Data generated with ScanCode require an acknowledgment.
+# ScanCode is a trademark of nexB Inc.
+#
+# You may not use this software except in compliance with the License.
+# You may obtain a copy of the License at: http://apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software distributed
+# under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
+# CONDITIONS OF ANY KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations under the License.
+#
+# When you publish or redistribute any data created with ScanCode or any ScanCode
+# derivative work, you must accompany this data with the following acknowledgment:
+#
+#  Generated with ScanCode and provided on an "AS IS" BASIS, WITHOUT WARRANTIES
+#  OR CONDITIONS OF ANY KIND, either express or implied. No content created from
+#  ScanCode should be considered or used as legal advice. Consult an Attorney
+#  for any legal advice.
+#  ScanCode is a free software code scanning tool from nexB Inc. and others.
+#  Visit https://github.com/nexB/scancode-toolkit/ for support and download.
+
+import os
+
+import psycopg2
+import json
+
+# Global Variables
+# To Format Query
+DATABASE_NAME = "clearcode_cditem"
+TOOL_NAME = "%/scancode/%"
+COLUMNS_RETURN = 'path, content'
+COLUMNS_SEARCH = "path"
+
+
+class PostgresFetch:
+
+    def __init__(self):
+        self.data_dir = os.path.join(os.path.dirname(__file__), 'data')
+        self.cursor, self.connection = self.init_connection()
+        self.offset = 0
+
+    def get_credentials_filepath(self):
+        """
+        Get credentials file os.Path object.
+
+        :returns file_path: os.Path object
+        """
+        file_path = os.path.join(self.data_dir, 'credentials.json')
+        return file_path
+
+    def import_database_credentials(self):
+        """
+        Fetch postgres Database credentials.
+
+        :returns credentials: JSON dict with credentials
+        """
+        file_path = self.get_credentials_filepath()
+
+        with open(file_path) as f:
+            credentials = json.load(f)
+
+        return credentials
+
+    def format_query(self, num_rows):
+        """
+        Formats query string using credentials and offset/row information.
+
+        :param num_rows: No of rows to Fetch from Postgres Database
+        :returns query_string: PostgreSQL query string
+        """
+        query_string = "SELECT {columns_return} FROM {database} WHERE {columns_search} like '{tool_name}'" \
+                       "OFFSET {offset} ROWS FETCH FIRST {num_rows} ROW ONLY;".format(
+                        columns_return=COLUMNS_RETURN,
+                        database=DATABASE_NAME,
+                        columns_search=COLUMNS_SEARCH,
+                        tool_name=TOOL_NAME,
+                        offset=self.offset,
+                        num_rows=num_rows
+                        )
+
+        return query_string
+
+    def init_connection(self):
+        """
+        Initiate Connection, called with Class Constructor.
+
+        :returns cursor: psycopg2.cursor Object
+        :returns connection: psycopg2.connection Object
+        """
+        # Fetch credentials from data/credentials.json
+        credentials = self.import_database_credentials()
+
+        # Initialize Connection Object
+        connection = psycopg2.connect(user=credentials['user'],
+                                      password=credentials['password'],
+                                      host=credentials['host'],
+                                      port=credentials['port'],
+                                      database=credentials['database'])
+
+        # Connect to Database
+        cursor = connection.cursor()
+
+        return cursor, connection
+
+    def fetch_data(self, num_rows_to_fetch):
+        """
+        Fetches `path` and `contents` from the Database, into list of Tuples. Example Tuple:
+        ('composer/packagist/phpro/grumphp/revision/0.16.1/tool/scancode/3.2.2.json', <memory at 0x7f222d6ccf48>)
+
+        :param num_rows_to_fetch: int
+            Number of rows to fetch, i.e. each row is a package scan
+        :returns records: list of tuples
+        """
+        # Fetch contents of rows where path has "/scancode/"
+
+        query_string = self.format_query(num_rows_to_fetch)
+        self.offset += num_rows_to_fetch
+        self.cursor.execute(query_string)
+
+        # Load all the data into record
+        records = self.cursor.fetchall()
+
+        return records
+
+    def close_connection(self):
+        """
+        Closes Postgres connection.
+        """
+        if self.connection:
+            self.cursor.close()
+            self.connection.close()
+            # print("PostgreSQL connection is closed")