BUG: unwanted type conversion when partial reassigning

[petrov826]

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• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

from typing import Union

import numpy as np
import pandas as pd

def get_sample_df():
    return pd.DataFrame(
        [
            ["1", np.nan],
            ["2", np.nan],
            ["3", np.nan],
            ["4", np.nan]
        ],
        dtype="object" # Reproduce the dataframe I'm working with.
    )

def try_cast_int(s: str) -> Union[int, str]:
    # some complex preprocessing here
    # I removed those to make my code shorter
    try:
        return int(s)
    except ValueError:
        return s

df = get_sample_df()

# Due to business reasons, apply `try_cast_int` only to the top half of `df`.
df.iloc[:2, :] = df.iloc[:2, :].applymap(try_cast_int)

Issue Description

Hello pandas team!

I found a bug(?) today. I expect that the df after the last line in the "Reproducible Example" will be a dataframe like below.

	0	1
0	1	np.NaN
1	2	np.NaN
2	3	np.NaN
3	4	np.NaN

But what I got was like below. I have no idea why I got float such like 1.0 and 2.0 instead of int.

	0	1
0	1.0	np.NaN
1	2.0	np.NaN
2	3	np.NaN
3	4	np.NaN

One interesting fact is df.iloc[:2, :].applymap(try_cast_int) before reassigning will return a dataframe like below.

	0	1
0	1	np.NaN
1	2	np.NaN

It seems that integers on the 1st column are converted into float values when partial reassigning.

My questions are

• Why type conversion happens?
• How can we avoid this behavior? (Is there any context manager or something for that?)

Expected Behavior

The df after the last line in the "Reproducible Example" will be a dataframe like below.

	0	1
0	1	np.NaN
1	2	np.NaN
2	3	np.NaN
3	4	np.NaN

I guess that "apply try_cast_int to the top half of df" is a cause of this issue. Pandas are not designed to do this kind of task, right?

---

I found that I can avoid this behavior and get what I want by following below steps.

1. spit the df into 2 before applying try_cast_int
2. apply try_cast_int to the top half of the df
3. No processing is done on the bottom half of the df
4. concat them into 1

example code

df = get_sample_df()

df_top = df.iloc[:2, :]
df_top = df_top.applymap(try_cast_int)

df_bottom = df.iloc[2:, :]

df_full = pd.concat([df_top, df_bottom], axis=0)

Best of luck.

Installed Versions

INSTALLED VERSIONS

commit : 66e3805
python : 3.8.16.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.133+
Version : #1 SMP Fri Aug 26 08:44:51 UTC 2022
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.3.5
numpy : 1.21.6
pytz : 2022.6
dateutil : 2.8.2
pip : 21.1.3
setuptools : 57.4.0
Cython : 0.29.32
pytest : 3.6.4
hypothesis : None
sphinx : 1.8.6
blosc : None
feather : 0.4.1
xlsxwriter : None
lxml.etree : 4.9.2
html5lib : 1.0.1
pymysql : None
psycopg2 : 2.9.5 (dt dec pq3 ext lo64)
jinja2 : 2.11.3
IPython : 7.9.0
pandas_datareader: 0.9.0
bs4 : 4.6.3
bottleneck : None
fsspec : 2022.11.0
fastparquet : None
gcsfs : None
matplotlib : 3.2.2
numexpr : 2.8.4
odfpy : None
openpyxl : 3.0.10
pandas_gbq : 0.17.9
pyarrow : 9.0.0
pyxlsb : None
s3fs : None
scipy : 1.7.3
sqlalchemy : 1.4.45
tables : 3.7.0
tabulate : 0.8.10
xarray : 2022.12.0
xlrd : 1.2.0
xlwt : 1.3.0
numba : 0.56.4

[phofl]

Hi, thanks for your report. This looks buggy, investigations are welcome.

Edit: Any reason you are not using astype here? Just asking, this should be much faster.

[petrov826]

@phofl Thank you for your response!

Any reason you are not using astype here? Just asking, this should be much faster.

Do you mean my custom function try_cast_int? It is sililar to .astype(int) but do some extra job. It removes , char to cast string like 3,000 to int 3000 and many more. We can achieve that by preprocessing strings by using df.str.replace(",", "") and .astype(int), though.

---

Edit: I want to do my best to parse integer string. If the value conversion fails, the value is supposed to be left as it is. This is why I don’t do in-place preprocessing.

I recognize that my try_cast_int clearly violates Single Responsibility Principle…

[phofl]

Ah got you, seemed a bit overcomplicated here but makes sense if you do more preprocessing