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