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Working with Dates and Times in Python

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

# Importing the course packages
import pandas as pd
import matplotlib.pyplot as plt
from datetime import date, datetime, timezone, timedelta
from dateutil import tz
import pickle

# Import the course datasets
rides = pd.read_csv('datasets/capital-onebike.csv')
with open('datasets/florida_hurricane_dates.pkl', 'rb') as f:
    florida_hurricane_dates = pickle.load(f)
florida_hurricane_dates = sorted(florida_hurricane_dates)
print(florida_hurricane_dates)

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

  • Count how many hurricanes made landfall each year in Florida using florida_hurricane_dates.
  • Reload the dataset datasets/capital-onebike.csv so that it correctly parses date and time columns.
  • Calculate the average trip duration of bike rentals on weekends in rides. Compare it with the average trip duration of bike rentals on weekdays.