课程

Introduction to Data Visualization with Matplotlib

基础技能水平

更新时间 2025年6月

Learn how to create, customize, and share data visualizations using Matplotlib.

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PythonData Visualization4 小时14 视频44 练习3,600 经验值220K+成就声明

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课程描述

Visualizing data in plots and figures exposes the underlying patterns in the data and provides insights. Good visualizations also help you communicate your data to others, and are useful to data analysts and other consumers of the data. In this course, you will learn how to use Matplotlib, a powerful Python data visualization library. Matplotlib provides the building blocks to create rich visualizations of many different kinds of datasets. You will learn how to create visualizations for different kinds of data and how to customize, automate, and share these visualizations.

先决条件

Introduction to Python

1

Introduction to Matplotlib

This chapter introduces the Matplotlib visualization library and demonstrates how to use it with data.

Introduction to data visualization with Matplotlib

50 经验值

Using the matplotlib.pyplot interface

100 经验值

Adding data to an Axes object

100 经验值

Customizing your plots

50 经验值

Customizing data appearance

100 经验值

Customizing axis labels and adding titles

100 经验值

Small multiples

50 经验值

Creating a grid of subplots

50 经验值

Creating small multiples with plt.subplots

100 经验值

Small multiples with shared y axis

100 经验值

2

Plotting time-series

Time series data is data that is recorded. Visualizing this type of data helps clarify trends and illuminates relationships between data.

Plotting time-series data

50 经验值

Read data with a time index

100 经验值

Plot time-series data

100 经验值

Using a time index to zoom in

100 经验值

Plotting time-series with different variables

50 经验值

Plotting two variables

100 经验值

Defining a function that plots time-series data

100 经验值

Using a plotting function

100 经验值

Annotating time-series data

50 经验值

Annotating a plot of time-series data

100 经验值

Plotting time-series: putting it all together

100 经验值

3

Quantitative comparisons and statistical visualizations

Visualizations can be used to compare data in a quantitative manner. This chapter explains several methods for quantitative visualizations.

Quantitative comparisons: bar-charts

50 经验值

100 经验值

Stacked bar chart

100 经验值

Quantitative comparisons: histograms

50 经验值

Creating histograms

100 经验值

"Step" histogram

100 经验值

Statistical plotting

50 经验值

Adding error-bars to a bar chart

100 经验值

Adding error-bars to a plot

100 经验值

Creating boxplots

100 经验值

Quantitative comparisons: scatter plots

50 经验值

Simple scatter plot

100 经验值

Encoding time by color

100 经验值

4

Sharing visualizations with others

This chapter shows you how to share your visualizations with others: how to save your figures as files, how to adjust their look and feel, and how to automate their creation based on input data.

Preparing your figures to share with others

50 经验值

Selecting a style for printing

50 经验值

Switching between styles

100 经验值

Saving your visualizations

50 经验值

Saving a file several times

100 经验值

Save a figure with different sizes

100 经验值

Automating figures from data

50 经验值

Unique values of a column

100 经验值

Automate your visualization

100 经验值

Where to go next

50 经验值

Introduction to Data Visualization with Matplotlib

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