I have Pandas DataFrame in Python like below:

col
-------
7.0
2.0
NaN
...

"col1" is in float data type but I would like to convert displaying of floar values in this column from for example 7.0 to 7. I can not simply change date type to int because I have also "NaN" values in col1.

So as a result I need something like below:

col
-------
7
2
NaN
...

How can I do that in Python Pandas ?

CodePudding user response：

You can use convert_dtypes to perform an automatic conversion:

df = df.convert_dtypes('col')

For all columns:

df = df.convert_dtypes()

output:

    col
0     7
1     2
2  <NA>

After conversion:

df.dtypes

col    Int64
dtype: object