Splitting a List inside a Pandas DataFrame

Question

I have a csv file that contains a number of columns. Using pandas, I read this csv file into a dataframe and have a datetime index and five or six other columns.

One of

Answer 1

Probably not the best way from performance perspective, but still, you can leverage itertools package:

from pandas import DataFrame, Timestamp
import itertools

d = {'date': ['4/1/11', '4/2/11'], 'ts': [[Timestamp('2012-02-29 00:00:00'), Timestamp('2012-03-31 00:00:00'), Timestamp('2012-04-25 00:00:00'), Timestamp('2012-06-30 00:00:00')], [Timestamp('2014-01-31 00:00:00')]]}
df = DataFrame(d)

res = df.to_dict()
data = []
for x in res['date'].keys():
  data.append(itertools.izip_longest([res['date'][x]], res['ts'][x], fillvalue=res['date'][x]))

new_data = list(itertools.chain.from_iterable(data))
df2 = DataFrame(new_data, columns=['date', 'timestamp'])
print df2

Will print :

     date  timestamp
0  4/1/11 2012-02-29
1  4/1/11 2012-03-31
2  4/1/11 2012-04-25
3  4/1/11 2012-06-30
4  4/2/11 2014-01-31