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# 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