Update: this has been fixed: from 0.11.1 you passing str
/np.str
will be equivalent to using object
.
Use the object dtype:
In [11]: pd.read_csv('a', dtype=object, index_col=0)
Out[11]:
A B
1A 0.35633069074776547 0.745585398803751
1B 0.20037376323337375 0.013921830784260236
or better yet, just don’t specify a dtype:
In [12]: pd.read_csv('a', index_col=0)
Out[12]:
A B
1A 0.356331 0.745585
1B 0.200374 0.013922
but bypassing the type sniffer and truly returning only strings requires a hacky use of converters
:
In [13]: pd.read_csv('a', converters={i: str for i in range(100)})
Out[13]:
A B
1A 0.35633069074776547 0.745585398803751
1B 0.20037376323337375 0.013921830784260236
where 100
is some number equal or greater than your total number of columns.
It’s best to avoid the str dtype, see for example here.