load_gdrive_csv.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import requests\n",
    "\n",
    "def extract_file_id(url):\n",
    "    \"\"\"Extract file id from Google Drive Sharing URL.\"\"\"\n",
    "    return url.split(\"/\")[-2]\n",
    "\n",
    "def df_from_gdrive_csv(url):\n",
    "    \"\"\" Get the CSV file from a Google Drive Sharing URL.\"\"\"\n",
    "    file_id = extract_file_id(url)\n",
    "    URL = \"https://docs.google.com/uc?export=download\"\n",
    "    session = requests.Session()\n",
    "    response = session.get(URL, params={\"id\": file_id}, stream=True)\n",
    "    return pd.read_csv(response.raw)\n",
    "\n",
    "# Example of how to use:\n",
    "sharing_url = \"https://drive.google.com/file/d/1RlilHNG7BtvXT2Pm4OpgNvEjVJJZNaps/view?usp=share_link\"\n",
    "df = df_from_gdrive_csv(sharing_url)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "\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>date</th>\n",
       "      <th>location</th>\n",
       "      <th>temperature</th>\n",
       "      <th>salinity</th>\n",
       "      <th>depth</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>Pacific</td>\n",
       "      <td>21.523585</td>\n",
       "      <td>NaN</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>Pacific</td>\n",
       "      <td>14.800079</td>\n",
       "      <td>34.467264</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>Pacific</td>\n",
       "      <td>23.752256</td>\n",
       "      <td>35.016505</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>Pacific</td>\n",
       "      <td>24.702824</td>\n",
       "      <td>36.416944</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>Pacific</td>\n",
       "      <td>10.244824</td>\n",
       "      <td>35.807487</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date location  temperature   salinity  depth\n",
       "0  2020-01-01  Pacific    21.523585        NaN    200\n",
       "1  2020-01-02  Pacific    14.800079  34.467264    100\n",
       "2  2020-01-03  Pacific    23.752256  35.016505    100\n",
       "3  2020-01-04  Pacific    24.702824  36.416944    200\n",
       "4  2020-01-05  Pacific    10.244824  35.807487   1000"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
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   "cell_type": "code",
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