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If you read in from a csv, you really should be able to just use df = read_csv('youcsv.csv').
Otherwise, not sure I follow your question.
-Harrison 9 years ago
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This is a source csv file
AAA;BBB1;BBB2;CCC1;CCC2;DDD1;DDD2 Some data;Some data;Some data;Some data;Some data;Some data;Some data Some data;Some data;Some data;Some data;Some data;Some data;Some data Some data;Some data;Some data;Some data;Some data;Some data;Some data Some data;Some data;Some data;Some data;Some data;Some data;Some data Some data;Some data;Some data;Some data;Some data;Some data;Some data Some data;Some data;Some data;Some data;Some data;Some data;Some data Some data;Some data;Some data;Some data;Some data;Some data;Some data Some data;Some data;Some data;Some data;Some data;Some data;Some data Some data;Some data;Some data;Some data;Some data;Some data;Some data Some data;Some data;Some data;Some data;Some data;Some data;Some data Some data;Some data;Some data;Some data;Some data;Some data;Some data
In the end I want to make a table with the merge of certain columns (BBB1 and BBB2 into BBB, CCC1 and CCC2 into CCC, DDD1 and DDD2 into DDD), similar to "colspan" in HTML.
-slevin.kelevra 9 years ago
Last edited 9 years ago
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Ah, I see. I really do not think Pandas will do this for you, unfortunately. Never seen something like that done at least.
-Harrison 9 years ago
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Decided that the formation of the structure of the table. Thank you :)
-slevin.kelevra 9 years ago
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