Best Practices With Pandas

Discover essential pandas techniques for data science tasks in this 90-minute tutorial. Master removing columns, comparing groups, examining relationships, handling missing values, utilizing string methods, combining dates and times, plotting time series, creating informative visualizations, and fixing bad data. Work with real-world datasets to avoid common pandas and data science pitfalls, enhancing your skills in data manipulation and analysis.

pandas best practices (1/10): Introducing the dataset.
pandas best practices (2/10): Removing columns.
pandas best practices (3/10): Comparing groups.
pandas best practices (4/10): Examining relationships.
pandas best practices (5/10): Handling missing values.
pandas best practices (6/10): Using string methods.
pandas best practices (7/10): Combining dates and times.
pandas best practices (8/10): Plotting a time series.
pandas best practices (9/10): Creating useful plots.
pandas best practices (10/10): Fixing bad data.