Series idxmin() TypeError?Need change type to 'float'

[rICHi97]

i'm using idxmin() on a series, which is like:

    ltc: 
    调度报障工单号
    DD182103227    5
                  ..
    DD082104265    5
    Name: 供电所, Length: 848, dtype: Int64

However, when using:
ltc.idxmin()

i got an error:
TypeError: argmin() takes 1 positional argument but 2 were given

when using:
ltc.astype('float').idxmin()

i got the right answer:
'DD092104104'

But the api doesn't say that idxmin() can only use on float data.Why?

[pablodz]

I tried to replicate the error but can't get it.

INPUT:

import pandas as pd
import numpy as np

df=pd.DataFrame({'col':['DD182103227','DD082104265'],
                'value':[5,4]},dtype=np.int64)
df.set_index('col')

OUTPUT:

             value
col               
DD182103227      5
DD082104265      4

INPUT:

df.info()

OUTPUT:

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 2 entries, 0 to 1
Data columns (total 2 columns):
 #   Column  Non-Null Count  Dtype 
---  ------  --------------  ----- 
 0   col     2 non-null      object
 1   value   2 non-null      int64 
dtypes: int64(1), object(1)
memory usage: 160.0+ bytes

INPUT:

df['value'].idxmin()

OUTPUT:

1

INPUT:

df['value'].astype('float').idxmin()

OUTPUT:

1

[rICHi97]

@ZurMaD
Thanks for your reply.
There is a difference between your test data and mine:
my data contains missing value, .
Tyr this code:
IN:
test = pd.Series([1, 2, None], dtype='Int64')
OUT:
0 1 1 2 2 <NA> dtype: Int64
IN:
test.idxmin()
OUT:
TypeError: argmin() takes 1 positional argument but 2 were given

Maybe integer dtypes and missing data causes this problem. But idxmin provides a skipna param and default is True, I don't know why it can't handle integer data.

[pablodz]

Related of #33719 and with a PR in #27801

Uhmm may someone of the main branch take a look? Looks like a BUG as described initially

But with example provided in docs works

https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.idxmin.html?highlight=series%20idxmin#pandas.Series.idxmin

Basically fails when dtype='Int64'

Output of pd.show_versions()

INSTALLED VERSIONS

commit : 2cb9652
python : 3.9.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.11.0-17-generic
Version : #18-Ubuntu SMP Thu May 6 20:10:11 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.2.4
numpy : 1.20.3
pytz : 2021.1
dateutil : 2.8.1
pip : 20.3.4
setuptools : 52.0.0
Cython : 0.29.23
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.1
IPython : 7.23.1
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.4.2
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyxlsb : None
s3fs : None
scipy : 1.6.3
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : None

[mzeitlin11]

This was fixed by #37924 with tests. (Fix is only in master, will be in 1.3)