230+ Exercises – Python for Data Science – NumPy + Pandas

Welcome to the 230+ Exercises – Python for Data Science – NumPy + Pandas course the place you possibly can check your Python programming abilities in information science, particularly in NumPy and Pandas.

Some numpy subjects you will see within the workout routines:

• working with numpy arrays
• producing numpy arrays
• producing numpy arrays with random values
• iterating by arrays
• coping with lacking values
• working with matrices
• studying/writing recordsdata
• becoming a member of arrays
• reshaping arrays
• computing fundamental array statistics
• sorting arrays
• filtering arrays
• picture as an array
• linear algebra
• matrix multiplication
• determinant of the matrix
• eigenvalues and eignevectors
• inverse matrix
• shuffling arrays
• working with polynomials
• working with dates
• working with strings in array
• fixing methods of equations

Some pandas subjects you will see within the workout routines:

• working with Collection
• working with DatetimeIndex
• working with DataFrames
• studying/writing recordsdata
• working with completely different information sorts in DataFrames
• working with indexes
• working with lacking values
• filtering information
• sorting information
• grouping information
• mapping columns
• computing correlation
• concatenating DataFrames
• calculating cumulative statistics
• working with duplicate values
• making ready information to machine studying fashions
• dummy encoding
• working with csv and json filles
• merging DataFrames
• pivot tables

The course is designed for individuals who have fundamental data in Python, NumPy and Pandas. It consists of 230 workout routines with options.

This can be a nice check for people who find themselves studying the Python language and information science and are trying for new challenges. Exercises are additionally check earlier than the interview. Many well-liked subjects have been coated on this course.

In case you’re questioning if it’s price taking a step in the direction of Python, don’t hesitate any longer and take the problem at the moment.