I have a pandas dataframe object that looks like this:
one two three four five
0 1 2 3 4 5
1 1 1 1 1 1
I'd like to generate a list of lists objects where the first item is the column label and the remaining list values are the column data values:
nested_list = [['one', 1, 1]
['two', 2, 1]
['three', 3, 1]
['four', 4, 1]
['five', 5, 1]]
How can I do this? Thanks for the help.
Simplest way is probably list(dt.T.itertuples()) (where dt is your dataframe). This generates a list of tuples.
@BrenBarn answer above yields a list of tuples not a list of list as asked in question. I specifically needed a list of lists to be able to write the dataframe into spreadsheed using DataNitro. Adapted the above example with list comprehension:
[list(x) for x in dt.T.itertuples()]
This yields the result as needed
Strictly speaking if you want nested lists (and not a list of tuples) you can do
df.values.tolist()
as df.values is a numpy array. That will give you a list of lists as requested:
[[0.0001313652121930252, 3.5915356549999985e-05],
[3.5915356549999985e-05, 0.00011634321240684215]]
My naive approach would be using iteritems with 'll' as a list of lists and l as a single list.
df = DataFrame({'one':[1,1], 'two':[2,1], 'three':[3,1], 'four':[3,1] })
ll = []
for idx,row in df.iteritems():
l = row.values.tolist()
l.insert(0,idx)
ll.append(l)
Old question I know, but this makes more sense to me than these other answers.
If this is your dataframe:
df = pd.DataFrame({'one': [1, 1], 'three': [3, 1], 'four': [4, 1],
'five': [5, 1], 'two': [2, 1]},
columns=['one', 'two', 'three', 'four', 'five'])
Do this:
df.T.reset_index().values.tolist()
Result
[['one', 1, 1], ['two', 2, 1], ['three', 3, 1], ['four', 4, 1], ['five', 5, 1]]
