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I have a nested list in this format mydata=[[01/01/20,['point1','point2','point3,...]],[02/01/20,['point1','point2','point3']],...] I want to create a pandas dataframe grouped by date with every point as a different row. I have tried manually adding each row through a for loop, but other than taking more than an hour, the dataframe ended up being empty. Not sure how to go about this. Can I create the grouped dataframe directly from the list?

My desired output would be:

    date          points

    01/01/20      point1
                  point2
                  point3
    02/01/20      point1
                  point2
                  point3
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1 Answer 1

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The expected output is not fully clear, but if I guess correctly:

mydata = [['01/01/20',['point1','point2','point3']],
          ['02/01/20',['point1','point2','point3']]]

df = pd.DataFrame(dict(mydata))

Or:

cols, data = zip(*mydata)

df = pd.DataFrame(zip(*data), columns=cols)

output:

  01/01/20 02/01/20
0   point1   point1
1   point2   point2
2   point3   point3
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8 Comments

This works great, thank you! How would I be able to pivot it so that I have it stacked with the dates on the left and points as individual rows on the right?
@Mary why don't you provide the exact explicit output in your question for clarity? ;)
Maybe you simply want pd.DataFrame.from_dict(dict(mydata), orient='index')?
Apologies, I have edited my question to show what output I'm looking for
OK, then pd.DataFrame(dict(mydata)).melt() or pd.DataFrame(dict(mydata)).stack()
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