Gain insights into using Python Pandas for efficient data analysis and manipulation. Delve into detailed functions, parameters, and methods to elevate your data handling skills.

A Comprehensive Practical Guide to Python Pandas_ .png

There are several exercises that focus on how to use a particular function and method. The functions are covered in detail by explaining the important parameters and how to use them. By completing this course, you will be able to do data analysis and manipulation with Pandas easily and efficiently.

Mastering Data Analysis with Python Pandas

# How to filter a `DataFrame` by condition

Recall the `sales` we’ve been using. It contains products that belong to one of six different product groups. Suppose we’re interested in only one product group and would like to filter products that belong to this group.

The following line of code selects the products that belong to product group `PG2`. Remember that each row in the sales represents a product.

```
sales_filtered = sales[sales.product_group == "PG2"]
```

The following line of code does the same operation.

```
sales_filtered = sales[sales["product_group"] == "PG2"]
```

We can use any of the options above, unless there’s a space in the column name. In such cases, the first option won’t work.

We can also filter a `DataFrame` based on numerical values. For instance, the following line of code selects the products with a price higher than 100.

 ```
sales_filtered = sales[sales["price"] > 100]
```

The operators we can use to create conditions are:
* `==`: equal
* `!=`: not equal
* `>`: greater than
* `>=`: greater than or equal to
* `<`: less than
* `<=`: less than or equal to



Learn how to filter values in a DataFrame based on a condition or a set of conditions. 

Filtering by Condition

Learn how to filter values in a DataFrame based on a condition or a set of conditions.

Course Introduction

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

Filtering by Condition

How to filter a `DataFrame` by condition

Filtering by Condition

How to filter a DataFrame by condition

How to filter a `DataFrame` by condition