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Python Data Science Toolbox (Part 1)
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  • Python Data Science Toolbox (Part 1)

    Run the hidden code cell below to import the data used in this course.

    # Import the course packages
    import pandas as pd
    from functools import reduce
    
    # Import the dataset
    tweets = pd.read_csv('datasets/tweets.csv')

    Take Notes

    Add notes about the concepts you've learned and code cells with code you want to keep.

    test

    Add your notes here

    # Add your code snippets here

    Explore Datasets

    Use the DataFrame imported in the first cell to explore the data and practice your skills!

    • Write a function that takes a timestamp (see column timestamp_ms) and returns the text of any tweet published at that timestamp. Additionally, make it so that users can pass column names as flexible arguments (*args) so that the function can print out any other columns users want to see.
    • In a filter() call, write a lambda function to return tweets created on a Tuesday. Tip: look at the first three characters of the created_at column.
    • Make sure to add error handling on the functions you've created!
    print(tweets.head())
    print(tweets.columns)
    tweets['text']