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

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