https://github.com/ananyachibber21/python-numpypandas-exercises

Exercises - Python for Data Science - NumPy + Pandas
https://github.com/ananyachibber21/python-numpypandas-exercises

numpy pandas python udemy

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Exercises - Python for Data Science - NumPy + Pandas

• Host: GitHub
• URL: https://github.com/ananyachibber21/python-numpypandas-exercises
• Owner: ananyachibber21
• Created: 2022-05-11T14:57:16.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-08-02T16:54:18.000Z (over 2 years ago)
• Last Synced: 2023-03-05T18:58:57.587Z (almost 2 years ago)
• Topics: numpy, pandas, python, udemy
• Language: Python
• Homepage:
• Size: 44.9 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Exercises - Python for Data Science - NumPy + Pandas

This is the Repository for the Udemy course: [Exercises - Python for Data Science - NumPy + Pandas](https://www.udemy.com/course/python-for-data-science-numpy-pandas-exercises/)

 

**Topics covered in Numpy:**

- working with numpy arrays

- generating numpy arrays

- generating numpy arrays with random values

- iterating through arrays

- dealing with missing values

- working with matrices

- reading/writing files

- joining arrays

- reshaping arrays

- computing basic array statistics

- sorting arrays

- filtering arrays

- image 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

- solving systems of equations

**Topics covered in Pandas:**

- working with Series

- working with DatetimeIndex

- working with DataFrames

- reading/writing files

- working with different data types in DataFrames

- working with indexes

- working with missing values

- filtering data

- sorting data

- grouping data

- mapping columns

- computing correlation

- concatenating DataFrames

- calculating cumulative statistics

- working with duplicate values

- preparing data to machine learning models

- dummy encoding

- working with csv and json filles

- merging DataFrames

- pivot tables