• Post category:StudyBullet-10
  • Reading time:4 mins read

Learn most powerful data analysis toolkit quickly and easily | All Codes, Jupyter notebooks and datasets are included

What You Will Learn

Learn fundamental concepts of data analysis

Learn to create dataframes and series

Learn importing data from multiple sources and transforming into Dataframe

Learn to perform data extraction

Learn removing missing values

Learn statistical analysis

Learn removing duplicate values

Learn data sorting

Learn indexing, slicing and data selection

Learn to create filters

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Learn to do export from dataframe to different file formats


  • Must have python and required python lib installed on system
  • Knowledge of sql would be helpful. But not neccessary.


Data analysis is a crucial thing in business to organize, interpret, structure and present the data to extract meaningful insights in order to take significant business decisions. With proper data analysis, organization could be able to

  • Predict customer behaviors
  • Market trend
  • Cut operational costs and resolve existing challenges
  • Build a better business plan, innovative sales and marketing strategies for the upcoming year and much more.

As per well renowned report, Data Analyst is forecast to be one of the most in-demand jobs by 2022. Even machine learning engineer and data scientist too needs data analysis skill. Because Data is new oil and it need to be processed.

With data analysis tools one can easily do data cleansing, data manipulation, data normalization, data inspection, statistical analysis, data fill and much more.

Pandas is one of the powerful library to do data analysis. In this learning course you’ll learn how to perform below mentioned tasks with Pandas in quick and easy way.

  • Importing data from multiple sources and transforming into Dataframe
  • Performing data extraction
  • Doing statistical analysis
  • Exporting dataframe into different file formats.
  • Creating filters
  • Doing Data inspection, data sorting, data visualization and much more.

Data analysis is an applied science, it requires lots of hands-on. In this course you’ll get lots of lot pragmatic hands-on in pythonic style.

See you in class!!

Who this course is for:

  • For data science, machine learning and data analytics enthuasist