[Free] Data Manipulation And Pca (Principal Component Analysis )
Data Manipulation and PCA – Free Course
What you’ll learn
- By the end of this course , a student will be able to do the following:
- Stet a working directory , Import a txt or csv file, eliminate duplicate rows in the data, detect rows containing missing values, eliminate rows containing missing values, replace missing values by the mean, replace missing values by a specified information, use the apply function , do some arithmetic on columns , detect strongly correlated variable (some nice plots for visualization ), compute the correlation matrix , the eigenvalue and eigenvector vector, select the number of components the compute the components
Requirements
- No Prior programing knowledge is required.
Description
In this course, we learn the following:How to Stet a working directory
How to Import a txt or csv file
How to eliminate duplicate rows in the data
How to detect rows containing missing values
How to eliminate rows containing missing values
How to replace missing values
How to select a subset of the data based on specifics criteria
How to do arithmetic on columns
How detect strongly correlated variable (some nice plots for visualization )
How to compute the correlation matrix , the eigenvalue and eigenvector
How select the number of components
How to compute the components
Author(s): Modeste Atsague
FREE
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