230+ Exercises – Python for Data Science – NumPy + Pandas
230+ Exercises – Python for Data Science – NumPy + Pandas, Double pack! Improve your Python programming and data science skills and solve over 230 exercises in NumPy and Pandas!
Welcome to the 230+ Exercises – Python for Data Science – NumPy + Pandas course where you can test your Python programming skills in data science, specifically in NumPy and Pandas.
Some numpy topics you will find in the exercises:
- 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
Some pandas topics you will find in the exercises:
- 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
The course is designed for people who have basic knowledge in Python, NumPy and Pandas. It consists of 230 exercises with solutions.
This is a great test for people who are learning the Python language and data science and are looking for new challenges. Exercises are also a good test before the interview. Many popular topics were covered in this course.
If you’re wondering if it’s worth taking a step towards Python, don’t hesitate any longer and take the challenge today.