Data Visualization with Python for Beginners

Data Visualization with Python for Beginners, available at $59.99, has an average rating of 4.51, with 56 lectures, based on 4754 reviews, and has 17567 subscribers.

You will learn about Make line plots in Python Make scatter plots in Python Make 1-dimensional and 2-dimensional histogram plots Customize your plots by adding colour and changing line styles Customize your axis by changing the tick labels Add custom titles and labels to your plots Add custom text to your plots Adjust the size of your figures Add a legend to your plots Be able to save your figures in a desired format to your computer Change the scale of the axis to better graph logarithmic data This course is ideal for individuals who are Anyone interested in analyzing data or Anyone who needs to visualize data or People who want to incorporate data visualization into their code or Anyone who is interested in expanding their Python knowledge It is particularly useful for Anyone interested in analyzing data or Anyone who needs to visualize data or People who want to incorporate data visualization into their code or Anyone who is interested in expanding their Python knowledge.

Enroll now: Data Visualization with Python for Beginners

Summary

Title: Data Visualization with Python for Beginners

Price: $59.99

Average Rating: 4.51

Number of Lectures: 56

Number of Published Lectures: 56

Number of Curriculum Items: 56

Number of Published Curriculum Objects: 56

Original Price: €29.99

Quality Status: approved

Status: Live

What You Will Learn

Make line plots in Python
Make scatter plots in Python
Make 1-dimensional and 2-dimensional histogram plots
Customize your plots by adding colour and changing line styles
Customize your axis by changing the tick labels
Add custom titles and labels to your plots
Add custom text to your plots
Adjust the size of your figures
Add a legend to your plots
Be able to save your figures in a desired format to your computer
Change the scale of the axis to better graph logarithmic data

Who Should Attend

Anyone interested in analyzing data
Anyone who needs to visualize data
People who want to incorporate data visualization into their code
Anyone who is interested in expanding their Python knowledge

Target Audiences

Anyone interested in analyzing data
Anyone who needs to visualize data
People who want to incorporate data visualization into their code
Anyone who is interested in expanding their Python knowledge

Data and analytics are becoming increasingly important in our world and in modern day businesses. Usually data analytics at one point or another also means including or creating graphics. This can help you get a better sense of the data as well as help you better communicate your findings to others.

Python is a favourite among data professionals, and performing analytics in Python is becoming increasingly more common. Therefore, it’s great to be able to also directly create custom graphs alongside all the analytics.

In this course we’ll start with some basic setup, and then get into different types of plots that we can create as well as how we can customize them.

We’ll start off covering basic line and scatter plots, just to get a hang of the library, and then move further to create a larger variety of graphs. You’ll learn how to add error bars, how to use and represent colours for intensities, how to use images in your plots, as well as how to create 3d plots.

Additionally, we’ll spend some time looking at the customization options that Matplotlib provides, so that we can change the way our axes and axis ticks and labels look, learn how to add annotations and math formulas, or also how to hide parts of a graph so that we have a reduced and cleaner version.

Course Curriculum

Chapter 1: Setup and Installation

Lecture 1: Introduction to Matplotlib and Installing Anaconda

Lecture 2: Jupyter Notebooks Intro

Lecture 3: Inline Plotting

Chapter 2: Line and Scatter Plots

Lecture 1: Making a Scatter Plot

Lecture 2: Understanding Figures

Lecture 3: Creating Axes

Lecture 4: Making a Line Plot

Lecture 5: Exercise Sheet 1 Intro

Lecture 6: Reading the Data From Txt File

Lecture 7: Reading the Data From CSV File

Lecture 8: Data Visualization Sheet 1 Exercise 1 Solution

Lecture 9: Data Visualization Sheet 1 Exercise 2 Solution

Chapter 3: Graph Customization, Annotation, and Formatting

Lecture 1: Changing the X and Y Limits

Lecture 2: Adding a Title and Axis Labels

Lecture 3: Adding in Equations Into Text

Lecture 4: Adding and Formatting Axis Ticks

Lecture 5: Customizing Tick Labels

Lecture 6: Data Visualization Exercise Sheet 2

Lecture 7: Data Visualization Sheet 2 Exercise 1 Solution

Lecture 8: Data Visualization Sheet 2 Exercise 2 Solution

Lecture 9: Adding a Legend

Lecture 10: Adding Text Annotations

Lecture 11: Customizing our Graph Edges

Lecture 12: Using Plot Styles

Lecture 13: Saving Our Plots

Lecture 14: Data Visualization Exercise Sheet 3

Lecture 15: Data Visualization Sheet 3 Datetime Intro

Lecture 16: Data Visualization Sheet 3 Exercise 1 Solution

Lecture 17: Data Visualization Sheet 3 Exercise 2 Solution Part 1

Lecture 18: Data Visualization Sheet 3 Exercise 2 Solution Part 2

Lecture 19: Data Visualization Sheet 3 Exercise 2 Solution Part 3

Lecture 20: Data Visualization Sheet 3 Exercise 3 Solution

Chapter 4: Histograms, Bar Graphs, Pie Charts, and Additional Graphs

Lecture 1: Histograms

Lecture 2: Advanced Histograms and Patches

Lecture 3: Bar Graphs

Lecture 4: Error Bars on Bar Graphs

Lecture 5: Box and Whisker Plots

Lecture 6: Pie Charts

Lecture 7: 2-Dimensional Histograms

Lecture 8: Data Visualization Exercise Sheet 4

Lecture 9: Data Visualization Sheet 4 Exercise 1 Sample Solution

Lecture 10: Data Visualization Sheet 4 Exercise 2 Sample Solution

Lecture 11: Data Visualization Sheet 4 Exercise 3 Sample Solution

Lecture 12: Data Visualization Sheet 4 Exercise 4 Sample Solution

Lecture 13: Data Visualization Sheet 4 Exercise 5 Sample Solution

Chapter 5: Images and Color Scales

Lecture 1: Loading and Showing Images

Lecture 2: Colormaps

Lecture 3: Adding a Colorbar to Our Axis

Lecture 4: Data Visualization Exercise Sheet 5

Lecture 5: Data Visualization Sheet 5 Exercise 1 Sample Solution

Lecture 6: Data Visualization Sheet 5 Exercise 2 Sample Solution Part 1

Lecture 7: Data Visualization Sheet 5 Exercise 2 Sample Solution Part 2

Chapter 6: 3D Graphing & Animating

Lecture 1: 3D Line and Scatter Plots

Lecture 2: Changing View Angles and Animating Our Graphs

Lecture 3: Data Visualization Exercise Sheet 6 Intro

Lecture 4: Data Visualization Sheet 6 Exercise 1 Sample Solution

Instructors

Max S
Data Engineer

Rating Distribution

1 stars: 26 votes
2 stars: 65 votes
3 stars: 576 votes
4 stars: 1876 votes
5 stars: 2210 votes

Frequently Asked Questions

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