Python_Pandas_Data_Structure_To_DataFrame.ipynb

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   "source": [
    "import pandas as pd\n",
    "\n",
    "# csv, excel, website, DB, JSON, API, CRM, Software, PDF, Doc"
   ]
  },
  {
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   "execution_count": 10,
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Numbers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>60</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Numbers\n",
       "0       10\n",
       "1       20\n",
       "2       30\n",
       "3       40\n",
       "4       50\n",
       "5       60"
      ]
     },
     "execution_count": 10,
     "metadata": {},
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   ],
   "source": [
    "# initialize list elements\n",
    "values = [10,20,30,40,50,60]\n",
    " \n",
    "# Create the pandas DataFrame with column name is provided explicitly\n",
    "df = pd.DataFrame(data=values, columns=['Numbers'])\n",
    " \n",
    "# print dataframe.\n",
    "df"
   ]
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Classes</th>\n",
       "      <th>Grades</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Chemistry</td>\n",
       "      <td>54.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Physics</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>History</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Geography</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>German</td>\n",
       "      <td>NaN</td>\n",
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       "     Classes  Grades\n",
       "1  Chemistry    54.0\n",
       "2    Physics    77.0\n",
       "3    History    22.0\n",
       "4  Geography    25.0\n",
       "5     German     NaN"
      ]
     },
     "execution_count": 17,
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   ],
   "source": [
    "subjects = [\"Mathematics\",\"Chemistry\",\"Physics\",\"History\",\"Geography\",\"German\"]\n",
    "classes = pd.Series(subjects)\n",
    "#print(subjects)\n",
    "#print(type(classes))\n",
    "grades  = pd.Series([90,54,77,22,25])\n",
    "\n",
    "pd.DataFrame(data={\"Classes\": classes[1:], \"Grades\": grades[1:]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
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       "      <th></th>\n",
       "      <th>Classes</th>\n",
       "      <th>Grades</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>first</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>second</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>third</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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      "text/plain": [
       "       Classes  Grades\n",
       "first      NaN     NaN\n",
       "second     NaN     NaN\n",
       "third      NaN     NaN"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "index1 = [\"first\", \"second\", \"third\"]\n",
    "subjects = pd.Series([\"Mathematics\",\"Chemistry\",\"Physics\"])\n",
    "grades = pd.Series([90,54,77])\n",
    "pd.DataFrame(data={\"Classes\": subjects, \"Grades\": grades}, index = index1) ## Does not work with index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    Mathematics\n",
       "1      Chemistry\n",
       "2        Physics\n",
       "dtype: object"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "subjects"
   ]
  },
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   "execution_count": 16,
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       "      <th>ID</th>\n",
       "      <th>Name</th>\n",
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       "    <tr>\n",
       "      <th>first</th>\n",
       "      <td>1</td>\n",
       "      <td>Jai</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>second</th>\n",
       "      <td>2</td>\n",
       "      <td>Veeru</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>third</th>\n",
       "      <td>3</td>\n",
       "      <td>Basanti</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>fourth</th>\n",
       "      <td>4</td>\n",
       "      <td>Gabbar</td>\n",
       "      <td>45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>five</th>\n",
       "      <td>5</td>\n",
       "      <td>Thakur</td>\n",
       "      <td>62</td>\n",
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      "text/plain": [
       "        ID     Name  Age\n",
       "first    1      Jai   32\n",
       "second   2    Veeru   31\n",
       "third    3  Basanti   24\n",
       "fourth   4   Gabbar   45\n",
       "five     5   Thakur   62"
      ]
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   "source": [
    "index_values = [\"first\", \"second\", \"third\", \"fourth\", \"five\"]\n",
    "a = {'ID':[1,2,3,4,5],\n",
    "  'Name':[\"Jai\",\"Veeru\",\"Basanti\",\"Gabbar\",\"Thakur\"],\n",
    "  'Age': [32,31,24,45,62]}\n",
    "\n",
    "sholay = pd.DataFrame(data = a, index =index_values)\n",
    "sholay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
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       "      <th></th>\n",
       "      <th>Name</th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Karan</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Rohit</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Sahil</td>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Aryan</td>\n",
       "      <td>24</td>\n",
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      "text/plain": [
       "    Name  Age\n",
       "0  Karan   23\n",
       "1  Rohit   22\n",
       "2  Sahil   21\n",
       "3  Aryan   24"
      ]
     },
     "execution_count": 26,
     "metadata": {},
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   ],
   "source": [
    "data_values = [['Karan',23],['Rohit',22],['Sahil',21],['Aryan',24]]\n",
    "\n",
    "df = pd.DataFrame(data = data_values, columns = ['Name','Age'])\n",
    "df"
   ]
  },
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   "cell_type": "code",
   "execution_count": 28,
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       "      <th>1</th>\n",
       "      <td>10</td>\n",
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       "      <td>67.0</td>\n",
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       "    a   b   c     d\n",
       "0   1   2   3   NaN\n",
       "1  10  20  30  67.0"
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   "source": [
    "# Initialize data to lists.\n",
    "data_values = [{'a': 1, 'b': 2, 'c': 3},\n",
    "        {'a': 10, 'b': 20, 'c': 30, 'd': 67}]\n",
    " \n",
    "# Creates DataFrame.\n",
    "df = pd.DataFrame(data_values)\n",
    " \n",
    "# Print the data\n",
    "df"
   ]
  },
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   "execution_count": 29,
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       "      <th>b</th>\n",
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       "      <th>a</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>first</th>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>second</th>\n",
       "      <td>20</td>\n",
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       "      <td>10.0</td>\n",
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       "         b   c     a\n",
       "first    2   3   NaN\n",
       "second  20  30  10.0"
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   "source": [
    "# Initialize data of lists\n",
    "data = [{'b': 2, 'c': 3}, {'a': 10, 'b': 20, 'c': 30}]\n",
    " \n",
    "# Creates pandas DataFrame by passing\n",
    "# Lists of dictionaries and row index.\n",
    "df = pd.DataFrame(data, index=['first', 'second'])\n",
    " \n",
    "# Print the data\n",
    "df"
   ]
  },
  {
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     "text": [
      "        a   b\n",
      "first   1   2\n",
      "second  5  10 \n",
      "\n",
      "        a  b1\n",
      "first   1 NaN\n",
      "second  5 NaN\n"
     ]
    }
   ],
   "source": [
    "# Initialize lists data.\n",
    "data = [{'a': 1, 'b': 2},\n",
    "        {'a': 5, 'b': 10, 'c': 20}]\n",
    " \n",
    "# With two column indices, values same\n",
    "# as dictionary keys\n",
    "df1 = pd.DataFrame(data, index=['first',\n",
    "                                'second'],\n",
    "                   columns=['a', 'b'])\n",
    " \n",
    "# With two column indices with\n",
    "# one index with other name\n",
    "df2 = pd.DataFrame(data, index=['first',\n",
    "                                'second'],\n",
    "                   columns=['a', 'b1'])\n",
    " \n",
    "# print for first data frame\n",
    "print(df1, \"\\n\")\n",
    " \n",
    "# Print for second DataFrame.\n",
    "print(df2)"
   ]
  },
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       "      <th>c</th>\n",
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       "      <th>d</th>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
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      "text/plain": [
       "   one  two\n",
       "a   10   10\n",
       "b   30   20\n",
       "c   20   30\n",
       "d   40   40"
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    }
   ],
   "source": [
    "# Initialize data to Dicts of series.\n",
    "one = [10, 20, 30, 40]\n",
    "oneSeries = pd.Series(one, index=['a', 'c', 'b', 'd'])\n",
    "d = {'one': oneSeries,\n",
    "     'two': pd.Series([10, 20, 30, 40],\n",
    "                      index=['a', 'b', 'c', 'd'])}\n",
    " \n",
    "# creates Dataframe.\n",
    "df = pd.DataFrame(d)\n",
    " \n",
    "# print the data.\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "E_szu8_6NxOF"
   },
   "outputs": [],
   "source": []
  }
 ],
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