Python for Data Visualization

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Michael Galarnyk and Madecraft

1:21:23

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01 - Introduction

01 - Effectively present data with Python.mp4

01:13

02 - Before you start.mp4

00:33

03 - Using the exercise files.mp4

00:27

02 - 1. Data Visualization Overview

01 - Value of data visualization.mp4

00:58

02 - Leverage programming languages.mp4

02:58

03 - Overview of Jupyter Notebooks.mp4

01:41

03 - 2. Leverage pandas for Analysis

01 - Introduction to pandas.mp4

01:30

02 - Create sample data.mp4

03:50

03 - Load sample data.mp4

02:17

04 - Basic operations.mp4

01:57

05 - Simplify with slicing.mp4

04:12

06 - Filter and clean data.mp4

05:39

07 - Rename and delete columns.mp4

03:16

08 - Aggregate functions.mp4

02:39

09 - Identify missing data.mp4

03:41

10 - Remove or fill in missing data.mp4

05:03

11 - Convert pandas DataFrames.mp4

01:15

12 - Export pandas DataFrames.mp4

01:28

04 - 3. Simplify Visualization with Matplotlib

01 - Basics of Matplotlib.mp4

03:49

02 - Set marker type and colors.mp4

01:52

03 - MATLAB-style vs. object syntax.mp4

02:07

04 - Set titles, labels, and limits.mp4

04:21

05 - Add grids.mp4

02:26

06 - Create legends.mp4

01:25

07 - Save plots to files.mp4

02:28

08 - Create plots with Matplotlib wrappers.mp4

05:00

05 - 4. Customize Visualizations with Matplotlib

01 - Create heatmaps.mp4

04:00

02 - Create histograms.mp4

03:33

03 - Create subplots.mp4

04:39

06 - Conclusion

01 - Next steps.mp4

01:06

Description

Data visualization is incredibly important for data scientists, as it helps them communicate their insights to nontechnical peers. But you don’t need to be a design pro. Python is a popular, easy-to-use programming language that offers a number of libraries specifically built for data visualization. In this course from the experts at Madecraft, you can learn how to build accurate, engaging, and easy-to-generate charts and graphs using Python. Explore the pandas and Matplotlib libraries, and then discover how to load and clean data sets and create simple and advanced plots, including heatmaps, histograms, and subplots. Instructor Michael Galarnyk provides all the instruction you need to create professional data visualizations through programming.

This course was created by Madecraft. We are pleased to host this content in our library.

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Python

Data Visualization

Michael Galarnyk and Madecraft

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