Reputation: 1223
If have a long dataframe, that features a two column multiindex and one column with values. I think this is the best way to represent data in pandas (tidy), but I'd like to convert it to a format that excel is capable of working with. The current format has too many rows. I start out with pandas in the first place, because i have about 6 GB of .csv data and excel won't do the job. A lot of it is cropped, so I hope the output is more manageable.
VALUE
DATE ID
2005-01-01 00:00:00 222 3.8
2005-01-01 01:00:00 222 3.7
2005-01-01 02:00:00 222 3.2
2005-01-01 00:00:00 201 3.1
2005-01-01 01:00:00 201 3.7
2005-01-01 02:00:00 201 3.2
...................................
The desired format for .csv export would look as follows:
201 222 ....
DATE
2005-01-01 00:00:00 3.1 3.8 ....
2005-01-01 01:00:00 3.7 3.7 ....
2005-01-01 02:00:00 3.2 3.2 ....
So in short, I'd like to convert every index value "ID" to a seperate column.
Upvotes: 1
Views: 31
Reputation: 863611
Select column VALUE
and reshape by Series.unstack
:
df1 = df['VALUE'].unstack()
If df
is Series
then use:
df1 = df.unstack()
Upvotes: 1