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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')



# Create a string: team
team = "teen titans"

# Define change_team()
def change_team():
    """Change the value of the global variable team."""

    # Use team in global scope
    global team

    # Change the value of team in global: team
    team = "justice league"
# Print team
print(team)


# Call change_team()
change_team()

# Print team
print(team)

Take Notes

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

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!