blockchain/Circulating Supply.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1498867200 1506816000\n",
      "1506816000 1514764800\n",
      "1514764800 1522713600\n",
      "1522713600 1530662400\n",
      "1530662400 1538611200\n",
      "1538611200 1546560000\n",
      "1546560000 1554508800\n",
      "1554508800 1562457600\n",
      "1562457600 1569508217\n"
     ]
    },
    {
     "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>timestamp</th>\n",
       "      <th>numHolders</th>\n",
       "      <th>circulatingSupply</th>\n",
       "      <th>totalSupply</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2017-06-30 17:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2017-07-01 17:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2017-07-02 17:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017-07-03 17:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2017-07-04 17:00:00</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            timestamp  numHolders  circulatingSupply  totalSupply\n",
       "0 2017-06-30 17:00:00           0                0.0          0.0\n",
       "1 2017-07-01 17:00:00           0                0.0          0.0\n",
       "2 2017-07-02 17:00:00           0                0.0          0.0\n",
       "3 2017-07-03 17:00:00           0                0.0          0.0\n",
       "4 2017-07-04 17:00:00           0                0.0          0.0"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import datetime\n",
    "import json\n",
    "import pandas as pd\n",
    "import requests\n",
    "\n",
    "# Download historical supplies in chunks (~90 days at a time)\n",
    "start_date=1498867200 # 2017/07/01 00:00:00\n",
    "last_date=1569508217  # 2019/09/26 14:30:17\n",
    "\n",
    "token_address=\"0xb8c77482e45f1f44de1745f52c74426c631bdd52\" # BNB token\n",
    "headers = {'content-type': 'application/json', 'x-api-key': '<ENTER_YOUR_API_KEY_HERE>'}\n",
    "frames = []\n",
    "\n",
    "while (start_date < last_date):\n",
    "    end_date = start_date + 7948800 # ~90 days\n",
    "    if (end_date > last_date):\n",
    "        end_date = last_date\n",
    "    print(start_date, end_date)\n",
    "\n",
    "    # Download historical supplies\n",
    "    url = \"https://web3api.io/api/v1/tokens/\" + token_address + \"/supplies/historical?startDate=\" + str(start_date) + \"&endDate=\" + str(end_date)\n",
    "    response = requests.get(url, headers=headers, verify=True)\n",
    "    if (not response.ok): # response.content, response.status_code\n",
    "        response.raise_for_status()\n",
    "\n",
    "    # Parse JSON data & save into array\n",
    "    jData = json.loads(response.content)\n",
    "    df = pd.DataFrame(jData['payload']['data'], columns=jData['payload']['metadata']['columns'])\n",
    "    frames.append(df)\n",
    "    \n",
    "    start_date = end_date\n",
    "\n",
    "# Concatenate all frames together\n",
    "df = pd.concat(frames, sort=False)\n",
    "df['timestamp'] = df['timestamp'].apply(lambda x: datetime.datetime.fromtimestamp(x/1000))\n",
    "df['circulatingSupply'] = df['circulatingSupply'].astype('float64')\n",
    "df['totalSupply'] = df['totalSupply'].astype('float64')\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Plot circulating and total supplies time series\n",
    "fig, ax = plt.subplots(figsize=(20, 10))\n",
    "ax = df.plot(ax=ax, kind='line', x='timestamp', y='circulatingSupply', c='Blue', grid=True, style='b')\n",
    "ax = df.plot(ax=ax, kind='line', x='timestamp', y='totalSupply',       c='Red',  grid=True, style='b')\n",
    "plt.show()\n",
    "\n",
    "# Plot num holders time series\n",
    "fig, ax = plt.subplots(figsize=(20, 10))\n",
    "ax = df.plot(ax=ax, kind='line', x='timestamp', y='numHolders', c='Blue', grid=True, style='b')\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
}