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

Table of Contents
Description
Welcome to the 230+ Exercises – Python for Data Science – NumPy + Pandas course the place you possibly can take a look at your Python programming abilities in information science, particularly in NumPy and Pandas.
Some numpy subjects one can find within the workout routines:
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working with numpy arrays
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producing numpy arrays
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producing numpy arrays with random values
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iterating by way of arrays
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coping with lacking values
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working with matrices
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studying/writing recordsdata
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becoming a member of arrays
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reshaping arrays
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computing fundamental array statistics
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sorting arrays
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filtering arrays
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picture as an array
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linear algebra
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matrix multiplication
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determinant of the matrix
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eigenvalues and eignevectors
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inverse matrix
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shuffling arrays
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working with polynomials
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working with dates
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working with strings in array
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fixing methods of equations
Some pandas subjects one can find within the workout routines:
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working with Collection
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working with DatetimeIndex
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working with DataFrames
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studying/writing recordsdata
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working with completely different information varieties in DataFrames
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working with indexes
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working with lacking values
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filtering information
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sorting information
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grouping information
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mapping columns
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computing correlation
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concatenating DataFrames
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calculating cumulative statistics
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working with duplicate values
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making ready information to machine studying fashions
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dummy encoding
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working with csv and json filles
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merging DataFrames
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pivot tables
The course is designed for individuals who have fundamental information in Python, NumPy and Pandas. It consists of 230 workout routines with options.
This can be a nice take a look at for people who find themselves studying the Python language and information science and are wanting for new challenges. Exercises are additionally a superb take a look at earlier than the interview. Many in style subjects have been lined on this course.
In case you’re questioning if it is price taking a step in direction of Python, do not hesitate any longer and take the problem right now.