Dataset after merging gives float values and cannot change to Int

Question

I have two dataset,

When i try to merge df3=pd.concat([df1, df2], axis=1, ignore_index= False)

I get the output as :

It gets automatically changed to float, and .astype("Int64"), doesnot change the float, is there any way to avoid this?

`df1` and `df2` are probably not the same length, so the sorter row is filled with `np.nan` and `np.nan` can't be converted by `.astype(int)`. You can `.dropna` or `fillna` and then change the type. — Trenton McKinney, Jul 10 '22 at 18:56

score 1 · Accepted Answer · answered Jul 10 '22 at 17:53

1

You can try and see:

df3.astype(int)

answered Jul 10 '22 at 17:53

Noob Coder

202
3
16

score 0 · Answer 2 · answered Jul 10 '22 at 17:52

0

Unable to reproduce your output

df1 = pd.DataFrame({"a": [100,20,30,5]})
df2 = pd.DataFrame({"b": [3,4,5,6]})
df3=pd.concat([df1, df2], axis=1, ignore_index= False)
print(df3)

     a  b
0  100  3
1   20  4
2   30  5
3    5  6

answered Jul 10 '22 at 17:52

Rajesh

766
5
17

score 0 · Answer 3 · answered Jul 10 '22 at 17:56

Can you add the output of df1.info() and df2.info()?
And print(df1.to_csv(index=False)) and print(df2.to_csv(index=False))?

That helps in reproducing the issue.

Seems to work fine without further details:

df1 = pd.DataFrame({'A':[100,20,30,5]})
df2 = pd.DataFrame({'B':[3,4,5,6]})
df3 = pd.concat([df1, df2], axis=1, ignore_index= False)
print(df3)

Result:

Dataset after merging gives float values and cannot change to Int

3 Answers3