Prevent pandas read_csv treating first row as header of column names

Question

I'm reading in a pandas DataFrame using pd.read_csv. I want to keep the first row as data, however it keeps getting converted to column names.

• I tried header=False but this just deleted it entirely.

(Note on my input data: I have a string (st = '\n'.join(lst)) that I convert to a file-like object (io.StringIO(st)), then build the csv from that file object.)

Answer 1

You want header=None the False gets type promoted to int into 0 see the docs emphasis mine:

header : int or list of ints, default ‘infer’ Row number(s) to use as the column names, and the start of the data. Default behavior is as if set to 0 if no names passed, otherwise None. Explicitly pass header=0 to be able to replace existing names. The header can be a list of integers that specify row locations for a multi-index on the columns e.g. [0,1,3]. Intervening rows that are not specified will be skipped (e.g. 2 in this example is skipped). Note that this parameter ignores commented lines and empty lines if skip_blank_lines=True, so header=0 denotes the first line of data rather than the first line of the file.

You can see the difference in behaviour, first with header=0:

In [95]: import io import pandas as pd t="""a,b,c 0,1,2 3,4,5""" pd.read_csv(io.StringIO(t), header=0)  Out[95]:    a  b  c 0  0  1  2 1  3  4  5 

Now with None:

In [96]: pd.read_csv(io.StringIO(t), header=None)  Out[96]:    0  1  2 0  a  b  c 1  0  1  2 2  3  4  5 

Note that in latest version 0.19.1, this will now raise a TypeError:

In [98]: pd.read_csv(io.StringIO(t), header=False) 

TypeError: Passing a bool to header is invalid. Use header=None for no header or header=int or list-like of ints to specify the row(s) making up the column names