Learn about DataFrames in the pandas library and how we can perform different operations on them.

Pandas: Python for Data Analysis

In this module, we’ll learn about DataFrames and their functions in detail. We’ll also learn to perform data manipulation and data visualization using pandas. We’ll solve several exercises that focus on how to use a DataFrame and its methods. By the end of this module, we’ll be able to do data analysis and manipulation with pandas easily and efficiently.

A Comprehensive Practical Guide to Python Pandas

Which parameter of the `concat` function is used to assign a new index to the combined `DataFrame`?

Which parameter of the <code>concat</code> function is used to assign a new index to the combined <code>DataFrame</code>?

Which option merges two `DataFrame`s in such a way that the resulting `DataFrame` will only have the values that exist in both `DataFrame`s?

Which option merges two <code>DataFrame</code>s in such a way that the resulting <code>DataFrame</code> will only have the values that exist in both <code>DataFrame</code>s?

Combining Pandas DataFrames

Combining Pandas DataFrames

Let's take a short quiz on what we've learned about combining DataFrames with Pandas.

Pandas Data Structures

Creating a Data Frame

Exploring a Data Frame

Filtering a Data Frame

String Manipulation with Pandas

Date Manipulation with Pandas

Handling Missing Values with Pandas

Data Analysis with Pandas

Data Visualization with Pandas

Combining DataFrames with Pandas

Final Challenge and Quiz

Conclusion

Quiz Yourself: Combining DataFrames with Pandas