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

Requirements

  • accomplished course ‘200+ Exercises – Programming in Python – from A to Z’
  • accomplished course ‘210+ Exercises – Python Customary Libraries – from A to Z’
  • accomplished course ‘150+ Exercises – Object Oriented Programming in Python – OOP’
  • fundamental data of NumPy and Pandas

Description

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.

Who this course is for:

  • everybody who needs to study by doing
  • everybody who needs to enhance Python programming abilities
  • everybody who needs to enhance information science abilities
  • everybody who needs to arrange for an interview

Get This Free Course

 

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