
Course Labs
Data Visualization in Python - The Complete Package
Learn python and how to use it to analyse, visualise and present data along with the use of Pandas, Numpy, Scipy.

Requirements
Basic experience with Microsoft Excel or another spreadsheet software (common functions, vlookups, Pivot Tables etc)
Interest in the Processing and Visualising of Real Data
You can learn this even if you don't know about basic level of Python programming
Description This comprehensive course will teach you how to use the power of Python to analyze data and create beautiful visualizations. Data scientist is the number one job on LinkedIn, among the World’s 100 most in-demand jobs, according to LinkedIn. The average salary of a Data Scientist is over $110,000 in the United States and all over the World. Data visualization is the discipline of attempting to comprehend information by setting it in a visual setting so that examples, patterns, and connections that could not, in any case, be identified can be uncovered. Python offers various extraordinary charting libraries loaded with bunches of various elements. Here are just a few of the topics we will be learning:
Programming with Python
NumPy with Python
Using Pandas Data Frames to solve complex tasks
Use Pandas to Files
Use matplotlib and Seaborn for data visualizations
Use Plotly and Cufflinks for interactive visualizations
Exploratory Data Analysis (EDA) of Boston Housing Dataset
Exploratory Data Analysis (EDA) of Titanic Dataset
Exploratory Data Analysis (EDA) of Latest Covid-19 Dataset
and much, much more!
By the end of this course you will:
Have an understanding of how to program in Python.
Know how to create and manipulate arrays using NumPy and Python.
Know how to use pandas to create and analyze data sets.
Know how to use matplotlib and seaborn libraries to create beautiful data visualization.
Have an amazing portfolio of python data analysis skills!
Have experience of creating a visualization of real-life projects
Data Visualization with Python - Course Curriculum 1. Introduction to Data Visualization
What is data visualization
Benefits of data visualization
Importance of data visualization
Top Python Libraries for Data Visualization
2. Matplotlib
Introduction to Matplotlib
Install Matplotlib with pip
Basic Plotting with Matplotlib
Plotting two or more lines on the same plot
3. Numpy and Pandas
What is NumPy?
Why use NumPy?
Installation of NumPy
Example of NumPy
What is a panda?
Key features of pandas
Python Pandas - Environment Setup
Pandas – Data Structure with example
4. Data Visualization tools
Bar chart
Histogram
Pie Chart
5. More Data Visualization tools
Scatter Plot
Area Plot
STACKED Area Plot
Box Plot
6. Advanced data Visualization tools
Waffle Chart
Word Cloud
HEAT MAP
7. Specialized data Visualization tools (Part-I)
Bubble charts
Contour plots
Quiver Plot
8. Specialized data Visualization tools (Part-II) Three-Dimensional Plotting in Matplotlib
3D Line Plot
3D Scatter Plot
3D Contour Plot
3D Wireframe Plot
3D Surface Plot
9. Seaborn
Introduction to seaborn
Seaborn Functionalities
Installing seaborn
Different categories of plot in Seaborn
Some basic plots using seaborn
10. Data Visualization using Seaborn
Strip Plot
Swarm Plot
Plotting Bivariate Distribution
Scatter plot, Hexbin plot, KDE, Regplot
Visualizing Pairwise Relationship
Box plot, Violin Plots, Point Plot
11. Project on Data Visualization Who this course is for:
Beginners python programmers.
Beginners Data Science programmers.
Anyone interested in learning in details about python, data science, or data visualizations.
Someone who want to work in analytics and visualization project.
Students Looking for Skill Development Courses