Analytics using Pandas and Numpy – Qualitative and Quantitative Studies

Learn to transform data into powerful dataframes specifically designed for recommendation and predictive applications.


This course facilitates major part of a data science project activity. In reality data scientists spend much of their time transforming, shaping-reshaping data to serve to several machine learning models. The activity to clean, transform and process the data will be the prime focus of this program. This program will also demonstrate simple to complex data visualizations using Pandas visualization library, seaborn library and matplotLib.
Numpy will be used to convert series data into N-dimensional arrays to feed into predictive models. Random numbers, math operations and statistics using Numpy will also be featured.


TECHNOLOGY USED: Python General Purpose, Anaconda Jupyter Notebooks, Pandas, Numpy

What Will I Learn?

  • Get familiar with data manipulation and numerical operations on multidimensional arrays
  • Learn to create data structures for Machine Learning
  • How to render visuals charts and their interpretations
  • Handle complex data formats
  • Build data reasoning

Topics for this course

40 Lessons20h

Introduction to Pandas

Installing and using Pandas
What are objects in Pandas
Objects example in Pandas i.e. Series Object, DataFrame & Index object

Data selections in Pandas

Data Group by and Aggregations

Handling Time Period data in Pandas

How to leverage Pandas for a Machine Learning Project?

Exploring Matplotlib

Exploring Seaborn

Numpy in Python

End of project

About the instructors

Pedagogy Trainings

4.67 ratings (6 )
23 Courses
83 students



Course Details


  • Python Core for Analytics

Target Audience

  • All working professionals wanting to know how to deal with data
  • Existing software coders and developers
  • Students & Professionals looking for a competitive edge in data science and Machine Learning