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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)
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.