Python MatPlotLib: For data analytics and data visualization

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Python MatPlotLib: For data analytics and data visualization
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.13 GB | Duration: 32 lectures • 3h 6m

Data analytics using Python MatPlotLib library and data visualization using Python MatPlotLib library

What you'll learn
Steps in data analytics
What is Matplotlib? Its interfaces.
Object Oriented Interface to Matplotlib
How to plot multiple plots
Types of formatting in plots
Types of plots using Matplotlib
How to plot three dimensional plots
Working with Non Numeric Data in Matplotlib

Requirements
Python programming language
Python numpy package
Description
The data analytics is the process of finding insights of the data. It involves following important steps,

1. Collection of relevant data

2. Preprocessing and transforming data

3. Plotting data using different types of graphs

4. Understanding insight of the data

We can plot data in different types of plots using MatPlotLib library. Matplotlib is a cross-platform, data visualization and graphical plotting library for Python and its numerical extension NumPy. It along with python numpy package provides open source alternative to MATLAB. Developers can use matplotlib library for plotting graphs. Also they can use matplotlib's APIs (Application Programming Interfaces) to embed plots in GUI based applications. In this course you are going to learn details of matplotlib library. The content of this course is as follows,

Chapter 1: Introduction to MatPlotLib

A. What is Matplotlib?

B. Pyploy API

C. PyLab Module

D. Simple Plot

Chapter 2: Object Oriented Matplotlib

A. Object oriented interface

B. Figure class

C. Axes class

D. Transforms

Chapter 3: Multiple Plots

A. Multiplots

B. Subplots function

C. Subplot2grid function

Chapter 4: Formatting Plots

A. Grids

B. Formatting axes

C. Setting limits

D. Setting ticks and tick labels

E. Twin axes

Chapter 5: Types of Plots

A. Bar plot

B. Stacked bar chart

C. Histogram

D. Pie chart

E. Scatter plot

F. Contour plot

G. Quiver plot

H. Box plot

I. Violin plot

Chapter 6: Three Dimensional Plotting

A. Three dimensional plotting

B. Three dimensional contour plot

C. Three dimensional wireframe plot

D. Three dimensional surface plot

Chapter 7: Working with Non Numeric Data

A. Working with text data

B. Working with mathematical expressions

C. Working with image data

Who this course is for
Under graduate students, working professional who want to learn data analytics

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