I'm working with a large csv file and the next to last column has a string of text that I want to split by a specific delimiter. I was wondering if there is a simple way to do this using pandas or python?
CustNum CustomerName ItemQty Item Seatblocks ItemExt
32363 McCartney, Paul 3 F04 2:218:10:4,6 60
31316 Lennon, John 25 F01 1:13:36:1,12 1:13:37:1,13 300
I want to split by the space (' ') and then the colon (':') in the Seatblocks column, but each cell would result in a different number of columns. I have a function to rearrange the columns so the Seatblocks column is at the end of the sheet, but I'm not sure what to do from there. I can do it in excel with the built in text-to-columns function and a quick macro, but my dataset has too many records for excel to handle.
Ultimately, I want to take records such John Lennon's and create multiple lines, with the info from each set of seats on a separate line.
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This splits the Seatblocks by space and gives each its own row.
In [43]: df
Out[43]:
CustNum CustomerName ItemQty Item Seatblocks ItemExt
0 32363 McCartney, Paul 3 F04 2:218:10:4,6 60
1 31316 Lennon, John 25 F01 1:13:36:1,12 1:13:37:1,13 300
In [44]: s = df['Seatblocks'].str.split(' ').apply(Series, 1).stack()
In [45]: s.index = s.index.droplevel(-1) # to line up with df's index
In [46]: s.name = 'Seatblocks' # needs a name to join
In [47]: s
Out[47]:
0 2:218:10:4,6
1 1:13:36:1,12
1 1:13:37:1,13
Name: Seatblocks, dtype: object
In [48]: del df['Seatblocks']
In [49]: df.join(s)
Out[49]:
CustNum CustomerName ItemQty Item ItemExt Seatblocks
0 32363 McCartney, Paul 3 F04 60 2:218:10:4,6
1 31316 Lennon, John 25 F01 300 1:13:36:1,12
1 31316 Lennon, John 25 F01 300 1:13:37:1,13
Or, to give each colon-separated string in its own column:
In [50]: df.join(s.apply(lambda x: Series(x.split(':'))))
Out[50]:
CustNum CustomerName ItemQty Item ItemExt 0 1 2 3
0 32363 McCartney, Paul 3 F04 60 2 218 10 4,6
1 31316 Lennon, John 25 F01 300 1 13 36 1,12
1 31316 Lennon, John 25 F01 300 1 13 37 1,13
This is a little ugly, but maybe someone will chime in with a prettier solution.