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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.

    Take Notes

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

    argumentos flexibles, se agrega un *args para determinar si llega o no un argumento o mas argumentos ***especiales

    def ver(*args):
    sum_all= 0
    for num in args:
        sum_all += num
    return sum_all
ver(2,3,2)

    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!