Data Visualization with Python for Beginners

Learn how to start visualizing all your data directly in your code
Data Visualization with Python for Beginners
File Size :
5.97 GB
Total length :
9h 31m

Category

Instructor

Maximilian Schallwig

Language

Last update

Last updated 4/2022

Ratings

4.4/5

Data Visualization with Python for Beginners

What you’ll 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

Data Visualization with Python for Beginners

Requirements

Basic Python knowledge
A Python 3 Environment to Code in

Description

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.

Overview

Section 1: Setup and Installation

Lecture 1 Introduction to Matplotlib and Installing Anaconda

Lecture 2 Jupyter Notebooks Intro

Lecture 3 Inline Plotting

Section 2: Line and Scatter Plots

Lecture 4 Making a Scatter Plot

Lecture 5 Understanding Figures

Lecture 6 Creating Axes

Lecture 7 Making a Line Plot

Lecture 8 Exercise Sheet 1 Intro

Lecture 9 Reading the Data From Txt File

Lecture 10 Reading the Data From CSV File

Lecture 11 Data Visualization Sheet 1 Exercise 1 Solution

Lecture 12 Data Visualization Sheet 1 Exercise 2 Solution

Section 3: Graph Customization, Annotation, and Formatting

Lecture 13 Changing the X and Y Limits

Lecture 14 Adding a Title and Axis Labels

Lecture 15 Adding in Equations Into Text

Lecture 16 Adding and Formatting Axis Ticks

Lecture 17 Customizing Tick Labels

Lecture 18 Data Visualization Exercise Sheet 2

Lecture 19 Data Visualization Sheet 2 Exercise 1 Solution

Lecture 20 Data Visualization Sheet 2 Exercise 2 Solution

Lecture 21 Adding a Legend

Lecture 22 Adding Text Annotations

Lecture 23 Customizing our Graph Edges

Lecture 24 Using Plot Styles

Lecture 25 Saving Our Plots

Lecture 26 Data Visualization Exercise Sheet 3

Lecture 27 Data Visualization Sheet 3 Datetime Intro

Lecture 28 Data Visualization Sheet 3 Exercise 1 Solution

Lecture 29 Data Visualization Sheet 3 Exercise 2 Solution Part 1

Lecture 30 Data Visualization Sheet 3 Exercise 2 Solution Part 2

Lecture 31 Data Visualization Sheet 3 Exercise 2 Solution Part 3

Lecture 32 Data Visualization Sheet 3 Exercise 3 Solution

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

Lecture 33 Histograms

Lecture 34 Advanced Histograms and Patches

Lecture 35 Bar Graphs

Lecture 36 Error Bars on Bar Graphs

Lecture 37 Box and Whisker Plots

Lecture 38 Pie Charts

Lecture 39 2-Dimensional Histograms

Lecture 40 Data Visualization Exercise Sheet 4

Lecture 41 Data Visualization Sheet 4 Exercise 1 Sample Solution

Lecture 42 Data Visualization Sheet 4 Exercise 2 Sample Solution

Lecture 43 Data Visualization Sheet 4 Exercise 3 Sample Solution

Lecture 44 Data Visualization Sheet 4 Exercise 4 Sample Solution

Lecture 45 Data Visualization Sheet 4 Exercise 5 Sample Solution

Section 5: Images and Color Scales

Lecture 46 Loading and Showing Images

Lecture 47 Colormaps

Lecture 48 Adding a Colorbar to Our Axis

Lecture 49 Data Visualization Exercise Sheet 5

Lecture 50 Data Visualization Sheet 5 Exercise 1 Sample Solution

Lecture 51 Data Visualization Sheet 5 Exercise 2 Sample Solution Part 1

Lecture 52 Data Visualization Sheet 5 Exercise 2 Sample Solution Part 2

Section 6: 3D Graphing & Animating

Lecture 53 3D Line and Scatter Plots

Lecture 54 Changing View Angles and Animating Our Graphs

Lecture 55 Data Visualization Exercise Sheet 6 Intro

Lecture 56 Data Visualization Sheet 6 Exercise 1 Sample Solution

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

Course Information:

Udemy | English | 9h 31m | 5.97 GB
Created by: Maximilian Schallwig

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