Basics of Matplotlib for Data Analysis & Data Science


Learn basics of Matplotlib ,frequent used Matplotlib plots , styling in Matplotlib with the help of real-world use-cases

English
language

What You Will Learn

Learn about Essentials of matplotlib to create plots like Bar Charts, Line Charts, Scatter Plots, Histogram ,distribution plots , and more!

How to customize matplotlib plots

Learn basic functionality when & where to use matplotlib

Learnbasic styling of matplotlib

Requirements

  • Have a Keen Desire to learn !

Description

In this course, you will learn how to create interactive Visuals in python using the Matplotlibly data visualizations library

This course will teach your everything you need to know to use Python to create interactive visuals  with Matplotlib. Have you ever wanted to take your Python skills to the next level in data visualization? With this course you will be able to create fully customization plots , interactive visuals with the open source libraries like Matplotlib

Data visualisation is very critical for generating and communicating easy to understand finding and insights. Either you are a Data Analyst who wants to create a dashboard/present your analysis or you are a Data Scientist who wants to create a UI for your machine learning models, Matplotlib can be a boon for both.

You will learn in this course many chart types..

  • Bar chart
  • Line cart
  • Pie chart
  • Scatter plot
  • Histogram
  • Box plot
  • Violin plot
  • Distribution (KDE) Plot

We’ll start off by teaching you enough Python and Pandas that you feel comfortable working and generating data  Then we’ll continue by teaching you about basic data visualization with Matplotlib, including scatter plots, line charts, bar charts , box plots, histograms, distribution plots and many more ! We’ll also give you an intuition of when to use each plot type.

By taking this course you will be learning the bleeding edge of data visualization technology with Python and gain a valuable new skill to show your colleagues or potential employers.


Subscribe to latest coupons on our Telegram channel.

Who this course is for:

  • Any Python programmers who want to present their analyses using interactive visualisation

Course content

6 sections • 15 lectures • 1h 55m total length

  • Introduction & course benefits !

    05:25

  • Quick Summary of Jupyter Notebook

    05:47

Enroll for Free

Share This Course on:
Ads Blocker Image Powered by Code Help Pro

Ads Blocker Detected!!!

We have detected that you are using extensions to block ads. Please support us by disabling these ads blocker.

Powered By
Best Wordpress Adblock Detecting Plugin | CHP Adblock