I have a situation wherein sometimes when I read a csv from df I get an unwanted index-like column named unnamed:0.
file.csv
,A,B,C
0,1,2,3
1,4,5,6
2,7,8,9
The CSV is read with this:
pd.read_csv('file.csv')
Unnamed: 0 A B C
0 0 1 2 3
1 1 4 5 6
2 2 7 8 9
This is very annoying! Does anyone have an idea on how to get rid of this?
It's the index column, pass pd.to_csv(..., index=False) to not write out an unnamed index column in the first place, see the to_csv() docs.
Example:
In [37]:
df = pd.DataFrame(np.random.randn(5,3), columns=list('abc'))
pd.read_csv(io.StringIO(df.to_csv()))
Out[37]:
Unnamed: 0 a b c
0 0 0.109066 -1.112704 -0.545209
1 1 0.447114 1.525341 0.317252
2 2 0.507495 0.137863 0.886283
3 3 1.452867 1.888363 1.168101
4 4 0.901371 -0.704805 0.088335
compare with:
In [38]:
pd.read_csv(io.StringIO(df.to_csv(index=False)))
Out[38]:
a b c
0 0.109066 -1.112704 -0.545209
1 0.447114 1.525341 0.317252
2 0.507495 0.137863 0.886283
3 1.452867 1.888363 1.168101
4 0.901371 -0.704805 0.088335
You could also optionally tell read_csv that the first column is the index column by passing index_col=0:
In [40]:
pd.read_csv(io.StringIO(df.to_csv()), index_col=0)
Out[40]:
a b c
0 0.109066 -1.112704 -0.545209
1 0.447114 1.525341 0.317252
2 0.507495 0.137863 0.886283
3 1.452867 1.888363 1.168101
4 0.901371 -0.704805 0.088335