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

Let's say we want to group the products in a `DataFrame` called `df` by the `color` and `brand` columns. What is the correct syntax for the `groupby` function for this case?

Let’s say we want to group the products in a <code>DataFrame</code> called <code>df</code> by the <code>color</code> and <code>brand</code> columns. What is the correct syntax for the <code>groupby</code> function for this case?

When using the `pivot_table` function to create a pivot table, which parameter is used to show the row and column subtotals?

When using the <code>pivot_table</code> function to create a pivot table, which parameter is used to show the row and column subtotals?

Which Pandas function is used to divide a column with continuous values into bins or categories with an approximately equal number of values?

Which Pandas function is used to divide a column with continuous values into bins or categories with an approximately equal number of values?

Which parameter is used to assign names to the categories or bins created by the `cut` and `qcut` functions?

Which parameter is used to assign names to the categories or bins created by the <code>cut</code> and <code>qcut</code> functions?

Data analysis with Pandas

Data analysis with Pandas

Let's take a short quiz on what we’ve learned about data analysis 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: Data Analysis with Pandas