python pandas dataframe from list of arrays

Question

I have a list as such:

[[None, 'ASK', 'BID'], ['4Y', 343.545, 344.621],['7Y', 0.016, 0.015],['9Y', 99.9, 99.8]]

and I would like to convert that into a dataframe as such:

'4Y' | 'ASK' | 343.545 '4Y' | 'BID' | 344.621 '7Y' | 'ASK' | 0.016 '7Y' | 'BID' | 0.015 '9Y' | 'ASK' | 99.9 '9Y' | 'BID' | 99.8

I've tried all sorts of "loopy" ways, but they seem terribly ugly and inefficient.

how about that it doesn't produce the expected outcome for a candidate, mate? — Simon Righley
– Simon Righley, Commented Nov 21, 2019 at 17:42
@DanielMesejo No, None is present only as the 0th element of the 0th sublist. — Simon Righley
– Simon Righley, Commented Nov 21, 2019 at 17:44
I don't think this question deserve downvoting. Someone may disagree with me. I give this an upvote to counteract the downvoting. — Andy L.
– Andy L., Commented Nov 21, 2019 at 17:59

Andy L. · Accepted Answer · 2019-11-21 17:48:15Z

5

Assume l is your list. Construct df and melt

df = pd.DataFrame(l[1:], columns=l[0])
df.rename({None: 'Year'}, axis=1).melt('Year').sort_values('Year')

Out[477]:
  Year variable    value
0   4Y      ASK  343.545
3   4Y      BID  344.621
1   7Y      ASK    0.016
4   7Y      BID    0.015
2   9Y      ASK   99.900
5   9Y      BID   99.800

answered Nov 21, 2019 at 17:48

Andy L.

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Comments

Quang Hoang · Accepted Answer · 2019-11-21 17:46:06Z

3

Takse some time to see what you want:

arr[0][0] = 'idx'
(pd.DataFrame(arr[1:], columns=arr[0])
   .set_index('idx')
   .stack()
   .reset_index(name='value')
)

Output:

  idx level_1    value
0  4Y     ASK  343.545
1  4Y     BID  344.621
2  7Y     ASK    0.016
3  7Y     BID    0.015
4  9Y     ASK   99.900
5  9Y     BID   99.800

answered Nov 21, 2019 at 17:46

Quang Hoang

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1 Comment

Quang Hoang Over a year ago

who said I downvoted? Not to mention that your question provide minimal information. You could have explained the out put.

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