Cleaning Data

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Damien Farrell edited this page Sep 1, 2015 · 1 revision

Pandas supports a variety of options for data 'cleaning' or dealing with missing data. The most basic are available from DataExplore from the main menu.

Currently available functions:

Drop rows/columns with missing data (NaNs)
Fill missing data with symbol
Forward or backfill with neighbouring values
Interpolate missing data
Drop duplicates

See Working with missing data