Skip to content

Data wrangling is used to convert data from an initial format to a format that may be better for analysis.

Notifications You must be signed in to change notification settings

Geidy/Python_DataWrangling

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 

Repository files navigation

Python_DataWrangling

Data wrangling is used to convert data from an initial format to a format that may be better for analysis.

Handle missing values Correct data formatting Standardize and normalize data

Binning Why binning? Binning is a process of transforming continuous numerical variables into discrete categorical 'bins' for grouped analysis.

Data Normalization Why normalization? Normalization is the process of transforming values of several variables into a similar range. Typical normalizations include scaling the variable so the variable average is 0 scaling the variable so the variance is 1 scaling the variable so the variable values range from 0 to 1

Data Standardization You usually collect data from different agencies in different formats. (Data standardization is also a term for a particular type of data normalization where you subtract the mean and divide by the standard deviation.) What is standardization? Standardization is the process of transforming data into a common format, allowing the researcher to make the meaningful comparison.

About

Data wrangling is used to convert data from an initial format to a format that may be better for analysis.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published