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Use pandas DataFrames on Excel Data

In this lab, we take a .csv file and create an Excel workbook out of it using pandas. The pdf of the notebook for this lab is [here.](

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Path Info

Clock icon Beginner
Clock icon 30m
Clock icon Mar 13, 2020

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Table of Contents

  1. Challenge

    Start Jupyter Notebook Server and Access on Your Local Machine

    Connecting to the Jupyter Notebook Server

    Make sure that you have activated the virtual environment!

    1. Use the following to activate the virtual environment:
    conda activate base
    1. To start the server, run the following:

    This is a simple script that starts the Jupyter notebook server and sets it to continue to run outside of the terminal.

    On the terminal is a token, please copy this and save it to a text file on your local machine.

    On Your Local Machine

    1. In a terminal window, enter the following:
    ssh -N -L localhost:8087:localhost:8086 cloud_user@<the public IP address of the Playground server>

    It will ask you for your password; this is the password you use to login to the Playground remote server.

    Leave this terminal open, it will appear nothing has happened, but it must remain open while you use the Jupyter Notebook server in this session.

    1. In the browser of your choice, enter the following address:


    This will open a Jupyter Notebook site that asks for the token you copied from the remote server.

  2. Challenge

    Read the File Into a DataFrame

    # open file for reading
    f = open('')
    # print the first two lines

    It appears the file is CSV. Read the file into a dataframe.

    import pandas as pd
    stock_df = pd.read_csv('')
  3. Challenge

    Create the Excel Workbook

    Create a dataframe for each of the requested stocks

    ge_df = stock_df[stock_df.stock=='GE']
    ibm_df = stock_df[stock_df.stock=='IBM']
    krft_df = stock_df[stock_df.stock=='KRFT']

    Write the Excel file

    with pd.ExcelWriter('stocks.xlsx') as writer:  
        ge_df.to_excel(writer, sheet_name='GE')
        ibm_df.to_excel(writer, sheet_name='IBM')
        krft_df.to_excel(writer, sheet_name='KRFT')
  4. Challenge

    Check the Excel Workbook Contains the Requested Data

    Load the file into an ordered dict dataframe and then check that each worksheet is populated.

    my_stock_df = pd.read_excel('stocks.xlsx', sheet_name=None)  

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