Advanced Techniques in pandas

Kursusindhold

Advanced Techniques in pandas

Advanced Techniques in pandas

1. Getting Familiar With Indexing and Selecting Data

Outputting Columns by Title Outputting Rows by Index Selecting Specific Rows and Columns Learning More About Indexation Getting Familiar With lambda Functions Expanding Functionality of the .iloc[] Attribute

2. Dealing With Conditions

Setting Condition Selecting Data Based on Condition Dealing With Several Conditions Making Your Code Beautiful Conditions Quiz

3. Extracting Data

Is Data in ...?Combining Your Knowledge Between Method Extracting Specific Data Finding the Smallest Values of a Column Finding the Largest Values of a Column Finding the Correlation

4. Aggregating Data

Getting Familiar With the .groupby() Method Grouping by Several Columns Complicated Grouping Advanced Grouping Dealing With Pivot Tables Creating a Pivot Table

5. Preprocessing Data

Checking for Missing Values Calculating the Number of Missing Values What Will We Do With the NaN Values?How to Delete Only NaN Values?Filling In the Missing Values Managing Categorical Variables Checking the Column Type Managing an Incorrect Column Renaming the Column

Outputting Columns by Title

You are already familiar with the functions that can output the dataset, but imagine you want to output only a specific column. Firstly, let's get acquainted with the dataset for this section. By the way, it is inconvenient to output the whole data set, so data analysts usually output a part of it to examine. In this course, we will usually output the first 5 rows.

Note

Some tables in the course, such as the one below, contain numerous columns. Therefore, you may need to scroll horizontally to see all the columns.

This table will help you understand how to output specific columns:

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Sektion 1. Kapitel 1

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Kursusindhold

Advanced Techniques in pandas

Advanced Techniques in pandas

1. Getting Familiar With Indexing and Selecting Data

Outputting Columns by Title Outputting Rows by Index Selecting Specific Rows and Columns Learning More About Indexation Getting Familiar With lambda Functions Expanding Functionality of the .iloc[] Attribute

2. Dealing With Conditions

Setting Condition Selecting Data Based on Condition Dealing With Several Conditions Making Your Code Beautiful Conditions Quiz

3. Extracting Data

Is Data in ...?Combining Your Knowledge Between Method Extracting Specific Data Finding the Smallest Values of a Column Finding the Largest Values of a Column Finding the Correlation

4. Aggregating Data

Getting Familiar With the .groupby() Method Grouping by Several Columns Complicated Grouping Advanced Grouping Dealing With Pivot Tables Creating a Pivot Table

5. Preprocessing Data

Checking for Missing Values Calculating the Number of Missing Values What Will We Do With the NaN Values?How to Delete Only NaN Values?Filling In the Missing Values Managing Categorical Variables Checking the Column Type Managing an Incorrect Column Renaming the Column

Outputting Columns by Title

You are already familiar with the functions that can output the dataset, but imagine you want to output only a specific column. Firstly, let's get acquainted with the dataset for this section. By the way, it is inconvenient to output the whole data set, so data analysts usually output a part of it to examine. In this course, we will usually output the first 5 rows.

Note

Some tables in the course, such as the one below, contain numerous columns. Therefore, you may need to scroll horizontally to see all the columns.

This table will help you understand how to output specific columns:

Var alt klart?

Tak for dine kommentarer!

Sektion 1. Kapitel 1

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