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Exercise: Resample Time-Series Data

Cesar Aguilar

The pandas DataFrame: Working With Data Efficiently Cesar Aguilar 08:00

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Course Contents

Overview

90%

The pandas DataFrame (Overview) 05:45

Setting Up Your Environment: Anaconda 02:00

Setting Up Your Environment: venv 05:13

Getting to Know pandas DataFrames 06:36

Working With Rows and Columns in DataFrames 04:28

Exercise: Access a DataFrame Row 08:00

Creating DataFrames 08:39

Creating DataFrames From CSV Files 03:56

Understanding DataFrame Attributes 08:02

Exercise: Create a DataFrame From a Dictionary 08:00

Modifying Values in DataFrames: Label Indices 04:44

Accessing Values in DataFrames 03:55

Modifying Values in DataFrames: Accessor Methods 05:43

Deleting and Inserting Rows in a DataFrame 05:21

Deleting and Inserting Columns in a DataFrame 05:16

Creating Columns With Arithmetic Operations and NumPy 06:20

Exercise: Add a Weighted Score Column 08:00

Sorting DataFrames 05:28

Filtering With Operators 05:25

Exercise: Filter and Sort Job Candidates 08:00

Filtering With .where() and .filter() 07:35

Using Statistical Methods on DataFrames 01:53

Handling Missing Data 08:16

Iterating Over Rows and Columns in DataFrames 07:37

Working With Time Series 03:23

Slicing DataFrames Using Datetime Indices 04:30

Exercise: Resample Time-Series Data 08:00

Doing Rolling-Window Analysis 04:31

Visualizing DataFrames With Matplotlib 04:35

The pandas DataFrame (Summary) 01:35

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