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Data Analysis with Pandas : Hands on Python

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Description

There are of Microsoft Excel is going to be over, so would you like to learn the next generation one of the most powerful data processing tool and in demand skill required for data analyst, data scientist and data engineer.

Then this course is for you, welcome to the course on data analysis with python's most powerful data processing library Pandas.


Why this course?

Data scientist is one of the hottest skill of 21st century and many organisation are switching their project from Excel to Pandas the advanced Data analysis tool .

This course is basically design to get you started with Pandas library  at beginner level,  covering majority of important concepts of data processing data analysis and a Pandas library and make you feel confident about data processing task with Pandas at advanced level.

What is this course?

This course covers

  • Basics of Pandas library

  • Python crash course for any of you want refresh basic concept of python

  • Python anaconda and Pandas installation

  • Detail understanding about two important data structure available in a Pandas library

  • Series data type

  • Data frame data type

  • How you can group the data for better analysis

  • How to use Pandas for text processing

  • How to visualize the data with Pandas inbuilt visualization tool

  • Multilevel index in Pandas.

This course has 80+ HD video lecture with 8+ hours of content and quizzes to to test your understanding about the videos.

This course is still in a draft mode. I am still adding more and more content, quiz, projects related to data processing with different functionalities of Pandas. So stay tuned and enroll now.

Regards

Ankit Mistry

Who this course is for:
  • Beginner Python developer who is curious about Data Science, Not for experienced Data Scientist
  • Anyone who want to make career in Data Science, Data analytics
  • Anyone wants to learn data analysis with python language
  • Excel user who wants to enhance data analysis skills.