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I have a dataframe with 3 columns: name, timestamp, value. It looks like this:

name - timestamp - value
A    - 1599810467 - 0.5
A    - 1599810468 - 1.5
B    - 1599810467 - 10
C    - 1599810469 - 4
A    - 1599810464 - 3
...

Now I want to turn names into columns, and basically merge on timestamp. Desired output:

timestamp  - A   - B   - C
1599810464 - 3   - NA  - NA
1599810467 - 0.5 - 10  - NA
1599810468 - 1.5 - NA  - NA
1599810469 - NA  - NA  - 4

Is there any way to do it natively in Pandas, or should I use Python to transform the values first?

double-beep
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Franc Weser
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1 Answers1

1

Okay figured it out:

df.pivot(index='timestamp', columns='name', values='value')

Franc Weser
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