Renaming column names in Pandas Dataframe

Question

I have the following table as input:

INPUT

Column1.ab.gz	Column2.ab.gz	Column3.ab.gz	Column4.ab.gz	Column5.ab.gz	Column6.ab.gz
1234	0	22	33	5	7
1235	1	2	2	0	234
1236	9	2	82	0	66
1237	0	0	0	0	0
1238	7	11	6	66	1
1239	5	27	5	0	8
1240	0	0	0	0	0
1241	15	0	2	13	5

I would like to rename the column name without 'ab.gz' automatically rather than renaming the column manually ( data.rename(columns = 'Column1.ab.gz':'Column1', 'Column2.ab.gz':'Column2', 'Column3.ab.gz':'Column3', 'Column4.ab.gz':'Column4', 'Column5.ab.gz':'Column5', 'Column6.ab.gz':'Column6') ) since the original table contains 50 columns. I would also like to remove the row which have all column value as 0.

The output should look something like the following:

OUTPUT

Column1	Column2	Column3	Column4	Column5	Column6
1234	0	22	33	5	7
1235	1	2	2	0	234
1236	9	2	82	0	66
1238	7	11	6	66	1
1239	5	27	5	0	8
1241	15	0	2	13	5

How do I do that in python?

Thanks in advance!

Answer 1

Use str.replace by empty string:

df.columns = df.columns.str.replace('.ab.gz', '')
print (df)
  Column1  Column2  Column3  Column4  Column5  Column6
0      aa        0       22       33        5        7
1      bb        1        2        2        0      234
2      cc        9        2       82        0       66
3      ee        0        0        0        0        0
4      ff        7       11        6       66        1
5      dd        5       27        5        0        8
6      aa        0        0        0        0        0
7      bb       15        0        2       13        5

If need values before first . :

df.columns = df.columns.str.split('.').str[0]

Answer 2

You can use list comprehension like this:

df.columns=[i.replace('.ab.gz','') for i in df.columns]