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pythonpandasdataframedata-science
VijayS
VijayS

Reputation: 25

Changing Pandas Data Frame Layout

I have a pandas dataframe that has four fields 'EventDate', 'DataField', 'DataValue'.

'DataField' has three values i.e Oxygen, HeartRate, HeartRateVariability.

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How to change the above format into following format for analysis?

enter image description here

Upvotes: 0

Views: 207

Answers (3)

Shivam Roy
Shivam Roy

Reputation: 2061

As suggested by others, you can use the pivot_table() function, specifically for your case you can try this:

pivot_df = df.pivot_table( index = 'EventDate', columns = 'DataField', values = 'DataValue')

Upvotes: 0

Aaron Diamond-Reivich
Aaron Diamond-Reivich

Reputation: 643

Any time you want to take one attribute in your dataset and group some other attributes by it, you should think about using pandas group_by or pivot_table functionality.

I'm personally a fan of pivot tables, so here is how do it in a pivot table:

# Pivot the data
pivot_table = df.pivot_table(
    index=['EventDate'],
    values=['Oxygen', 'HeartRate', 'HeartRateVariability],
    aggfunc={'Oxygen': 'mean', 'HeartRate': 'mean', 'HeartRateVariability': 'mean'}
)

By specifying the aggfunc as mean, if there are any EventDates that have multiple records, the resulting pivot table will have the mean of those records listed.

If creating pivot tables is something you do often, you could also checkout some pandas pivot table GUIs. I'm the creator of one called Mito. Mito is an extension to Jupyter Lab and it lets you create pivot tables (and other spreadsheet style analyses) in a point and click way. Each time you make an edit in the Mito spreadsheet, it automatically generates the equivalent pandas code for you.

Upvotes: 1

Nk03
Nk03

Reputation: 14949

you can try pivot :

df = df.pivot(*df).fillna('')

For more info -> you can check pivot & pivot_table

Upvotes: 1

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