blockchain/Account Balances.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import requests\n",
    "\n",
    "# Retrieve data from API\n",
    "wallet_address='0x3f5ce5fbfe3e9af3971dd833d26ba9b5c936f0be'\n",
    "url = \"https://web3api.io/api/v1/addresses/\" + wallet_address + \"/account-balances/historical?includePrice=true\"\n",
    "headers = {'content-type': 'application/json', 'x-api-key': '<ENTER_YOUR_API_KEY_HERE>'}\n",
    "\n",
    "response = requests.get(url, headers=headers, verify=True)\n",
    "if (not response.ok): # response.status_code\n",
    "    response.raise_for_status()\n",
    "\n",
    "# Parse JSON data\n",
    "jData = json.loads(response.content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>address</th>\n",
       "      <th>blockNumber</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>timestampNanoseconds</th>\n",
       "      <th>value</th>\n",
       "      <th>price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0x3f5ce5fbfe3e9af3971dd833d26ba9b5c936f0be</td>\n",
       "      <td>8644858</td>\n",
       "      <td>2019-09-29 09:55:13</td>\n",
       "      <td>0</td>\n",
       "      <td>9.129411e+22</td>\n",
       "      <td>1.554745e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0x3f5ce5fbfe3e9af3971dd833d26ba9b5c936f0be</td>\n",
       "      <td>8644852</td>\n",
       "      <td>2019-09-29 09:53:40</td>\n",
       "      <td>0</td>\n",
       "      <td>9.129412e+22</td>\n",
       "      <td>1.554571e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0x3f5ce5fbfe3e9af3971dd833d26ba9b5c936f0be</td>\n",
       "      <td>8644851</td>\n",
       "      <td>2019-09-29 09:53:34</td>\n",
       "      <td>0</td>\n",
       "      <td>9.129454e+22</td>\n",
       "      <td>1.554578e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0x3f5ce5fbfe3e9af3971dd833d26ba9b5c936f0be</td>\n",
       "      <td>8644848</td>\n",
       "      <td>2019-09-29 09:52:23</td>\n",
       "      <td>0</td>\n",
       "      <td>9.129455e+22</td>\n",
       "      <td>1.554579e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0x3f5ce5fbfe3e9af3971dd833d26ba9b5c936f0be</td>\n",
       "      <td>8644844</td>\n",
       "      <td>2019-09-29 09:51:57</td>\n",
       "      <td>0</td>\n",
       "      <td>9.129455e+22</td>\n",
       "      <td>1.554579e+07</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      address blockNumber           timestamp  \\\n",
       "0  0x3f5ce5fbfe3e9af3971dd833d26ba9b5c936f0be     8644858 2019-09-29 09:55:13   \n",
       "1  0x3f5ce5fbfe3e9af3971dd833d26ba9b5c936f0be     8644852 2019-09-29 09:53:40   \n",
       "2  0x3f5ce5fbfe3e9af3971dd833d26ba9b5c936f0be     8644851 2019-09-29 09:53:34   \n",
       "3  0x3f5ce5fbfe3e9af3971dd833d26ba9b5c936f0be     8644848 2019-09-29 09:52:23   \n",
       "4  0x3f5ce5fbfe3e9af3971dd833d26ba9b5c936f0be     8644844 2019-09-29 09:51:57   \n",
       "\n",
       "   timestampNanoseconds         value         price  \n",
       "0                     0  9.129411e+22  1.554745e+07  \n",
       "1                     0  9.129412e+22  1.554571e+07  \n",
       "2                     0  9.129454e+22  1.554578e+07  \n",
       "3                     0  9.129455e+22  1.554579e+07  \n",
       "4                     0  9.129455e+22  1.554579e+07  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import datetime\n",
    "import pandas as pd\n",
    "\n",
    "# Load & transform JSON data into Data Frame\n",
    "df = pd.DataFrame(jData['payload']['data'], columns=jData['payload']['metadata']['columns'])\n",
    "df['timestamp'] = df['timestamp'].apply(lambda x: datetime.datetime.fromtimestamp(x/1000))\n",
    "df['price'] = df['price'].astype('float64')\n",
    "df['value'] = df['value'].astype('float64')\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Plot account balance time series\n",
    "fig, ax = plt.subplots(figsize=(20, 10))\n",
    "ax = df.plot(ax=ax, kind='line', x='timestamp', y='price', c='Blue', grid=True, style='b')\n",
    "ax = df.plot(ax=ax, kind='line', x='timestamp', y='value', c='Red',  grid=True, style='b', secondary_y=True)\n",
    "plt.show()"
   ]
  }
 ],
 "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": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}