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Python Data Science Toolbox (Part 1)

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

1 hidden cell

Take Notes

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

Add your notes here

# Define shout_echo
def shout_echo(word1, echo=1, intense=False):
    """Concatenate echo copies of word1 and three
    exclamation marks at the end of the string."""

    # Concatenate echo copies of word1 using *: echo_word
    echo_word = word1 * echo

    # Make echo_word uppercase if intense is True
    if intense is True:
        # Make uppercase and concatenate '!!!': echo_word_new
        echo_word_new = echo_word.upper() + '!!!'
    else:
        # Concatenate '!!!' to echo_word: echo_word_new
        echo_word_new = echo_word + '!!!'

    # Return echo_word_new
    return echo_word_new

# Call shout_echo() with "Hey", echo=5 and intense=True: with_big_echo
with_big_echo = shout_echo("Hey", echo=5, intense=True)

# Call shout_echo() with "Hey" and intense=True: big_no_echo
big_no_echo = shout_echo("Hey", intense=True)

# Print with_big_echo and big_no_echo
print(with_big_echo)
print(big_no_echo)

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!