Connect Jupyter Notebook with Google Sheet

Google_Drive.ipynb

{
  "cells": [
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# Import libraries \nimport pandas as pd\nimport warnings\nwarnings.filterwarnings(\"ignore\")\n# For connect to google sheet\nimport gspread\nfrom oauth2client.service_account import ServiceAccountCredentials\nfrom df2gspread import df2gspread as d2g",
      "execution_count": 19,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# Configure the connection \nscope = ['https://spreadsheets.google.com/feeds']\n\n# Give the path to the Service Account Credential json file \ncredentials = ServiceAccountCredentials.from_json_keyfile_name('key/service_account_GS.json',\n                                                               scope\n                                                              )\n# Authorise your Notebook\ngc = gspread.authorize(credentials)\n\n# The sprad sheet ID, which can be taken from the link to the sheet\nspreadsheet_key = '1pwJDzIl1O8gQSHD8SekW6442rrLRgLVTYA90dQb7chg'",
      "execution_count": 20,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# Read some data from a csv file into a pandas dataframe\n# In this case, we read in the client IDs we got in the Blog \n#\"Get Google Analytics data to your Jupyter Notebook by using Analytics Reporting API\"\ndf = pd.read_csv('client_ids.csv',index_col = False)",
      "execution_count": 21,
      "outputs": []
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "df.head()",
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "execution_count": 22,
          "data": {
            "text/plain": "      client_ID\n0  1.001033e+09\n1  1.001090e+09\n2  1.007582e+09\n3  1.010111e+09\n4  1.014999e+08",
            "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>client_ID</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>1.001033e+09</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1.001090e+09</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>1.007582e+09</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1.010111e+09</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>1.014999e+08</td>\n    </tr>\n  </tbody>\n</table>\n</div>"
          },
          "metadata": {}
        }
      ]
    },
    {
      "metadata": {
        "trusted": true
      },
      "cell_type": "code",
      "source": "# Set the sheet name you want to upload data to and the start cell where the upload data begins \nwks_name = 'Sheet1'\ncell_of_start_df = 'A2'\n# upload the dataframe of the clients we want to delete\nd2g.upload(df,\n           spreadsheet_key,\n           wks_name,\n           credentials=credentials,\n           col_names=False,\n           row_names=False,\n           start_cell = cell_of_start_df,\n           clean=False)\nprint ('The sheet is updated successfully')",
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "text": "The sheet is updated successfully\n",
          "name": "stdout"
        }
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3",
      "language": "python"
    },
    "language_info": {
      "name": "python",
      "version": "3.6.4",
      "mimetype": "text/x-python",
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "pygments_lexer": "ipython3",
      "nbconvert_exporter": "python",
      "file_extension": ".py"
    },
    "latex_envs": {
      "eqNumInitial": 1,
      "eqLabelWithNumbers": true,
      "current_citInitial": 1,
      "cite_by": "apalike",
      "bibliofile": "biblio.bib",
      "LaTeX_envs_menu_present": true,
      "labels_anchors": false,
      "latex_user_defs": false,
      "user_envs_cfg": false,
      "report_style_numbering": false,
      "autoclose": false,
      "autocomplete": true,
      "hotkeys": {
        "equation": "Ctrl-E",
        "itemize": "Ctrl-I"
      }
    },
    "gist": {
      "id": "",
      "data": {
        "description": "Connect Jupyter Notebook with Google Sheet",
        "public": true
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 2
}