## Intermediate pandas

INTERMEDIATE

#python

Author: Diana Sadyrova

Course description

This course contains a lot of useful functions for a future data analyst. You will learn different ways of extracting data and even set conditions on it. After it, you will be familiar with the methods of grouping data. Also, you will learn how to preprocess data. Each section has its data set so that the course will be gripping.

Complete all chapters to get certificate

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Get Familiar With Indexing and Selecting Data

This section will teach you how to output specific columns by their titles or indices. Also, you will get acquainted with the ways you can select rows by indices.

Output Columns by Title

Output Rows by Index

Select Specific Rows and Columns

Learn More About Indexation

Get Familiar With lambda Functions

Expand Functionality of the .iloc[] Function

Dealing With Conditions

Here, you will learn how to extract data that has specific conditions. Also, you will learn how to combine them and even create your own.

Set Condition

Challenge

Dealing With Several Conditions

Make Your Code Beautiful

Challenge

Extract Data

In this section, you will expand your knowledge on setting different data conditions. You will learn to check if your data is in a defined list of values or between two values. You will also learn how to find the largest and smallest values.

Is Data in ...?

Combine Your Knowledge

Between Function

Challenge

Find the Smallest Values of a Column

Find the Largest Values of a Column

Find the Correlation

Aggregating Data

This section is one of the most fascinating of the course. Here, you will learn how to group data in different ways. It will help you work as a data analyst to find out information on specific data groups.

Get Familiar With the .groupby() Function

Group by Several Columns

Complicated Grouping

Group

Dealing With Pivot Tables

Challenge

Preprocessing Data

This section is one of the most significant for a data analyst because if the data contains missing data values in the incorrect format, it will be impossible to work with. Thus, you will learn how to deal with such inappropriate values here.

Check for Missing Values

Calculate the Number of Missing Values

What Will We Do With the NaN Values?

How to Delete Only NaN Values?

Fill In the Missing Values

Manage Categorical Variables

Check the Column Type

Manage an Incorrect Column

Rename the Column