Data Manipulation and PCA (Principal Component Analysis )

Data Manipulation and PCA

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

In this course, we learn the following:

How toStet a working directory

How toImport a txt or csv file

How toeliminate duplicate rows in the data

How to detect rows containing missing values

How toeliminate rows containing missing values

How toreplace missing values

How to select a subset of the data basedon specifics criteria

How todo arithmetic on columns

Howdetect strongly correlated variable (some nice plots for visualization )

How tocompute the correlation matrix , the eigenvalue and eigenvector

How select the number of components

How tocompute the components