How can I split text in a column into multiple rows using Pandas and Python?

Splitting Text in a Column into Multiple Rows

When working with large CSV files, it can be necessary to split text in a specific column into multiple rows. Pandas and Python offer efficient methods to accomplish this task.

Using Pandas

1. Split by Space:

   df['Seatblocks'].str.split(' ').apply(Series, 1).stack()

   This splits each row in the 'Seatblocks' column by space and creates a new column for each resulting string.

2. Split by Colon:

   df['Seatblocks'].str.split(' ').apply(lambda x: Series(x.split(':')))

   This further splits each string in the new column by colon, creating multiple columns for each colon-separated string.

Example

Consider this CSV file:

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

Using the above methods, the 'Seatblocks' column can be split into multiple rows:

CustNum	CustomerName	ItemQty	Item	Seatblocks1	Seatblocks2	Seatblocks3	Seatblocks4	ItemExt
32363	McCartney, Paul	3	F04	2	218	10	4,6	60
31316	Lennon, John	25	F01	1	13	36	1,12	300
31316	Lennon, John	25	F01	1	13	37	1,13	300

Conclusion

By utilizing Pandas' splitting and stacking operations, it is possible to efficiently restructure text data in a column into multiple rows, enabling further analysis and manipulation.

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