• [x] I have checked that this issue has not already been reported.
  • [x] I have confirmed this bug exists on the latest version of pandas.
  • [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

Code Sample, a copy-pastable example

# import pandas as pd
# import numpy as np

# like https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.cumsum.html
# Ex1
>>> pd.Series([2, np.nan, 5, -1, 0], dtype="float").cumsum()
0    2.0
1    NaN
2    7.0
3    6.0
4    6.0
dtype: float64

# Ex2
>>> pd.Series([2, np.nan, 5, -1, 0], dtype="Float64").cumsum()
0    2.0
1    2.0
2    7.0
3    6.0
4    6.0
dtype: object

# Ex3
>>> pd.Series([2, np.nan, 5, -1, 0], dtype="Int64").cumsum()
0       2
1    <NA>
2    <NA>
3    <NA>
4    <NA>
dtype: object

Problem description

  • Ex1 is expected behavior while Ex2 and Ex3 yield different values.
  • Ex2 returns dtype: object but Float64 is expected, the same applies to Ex3.
  • Other cum-family methods (cumprod, cummax, cummin) have the same problem.

Expected Output

# Ex2
>>> pd.Series([2, np.nan, 5, -1, 0], dtype="Float64").cumsum()
0    2.0
1    <NA>
2    7.0
3    6.0
4    6.0
dtype: Float64

# Ex3
>>> pd.Series([2, np.nan, 5, -1, 0], dtype="Int64").cumsum()
0       2
1    <NA>
2       7
3       6
4       6
dtype: Int64

Environment

FROM python:3.9.1-slim-buster
WORKDIR /home
RUN pip install pandas==1.2.1
CMD ["/usr/local/bin/python"]

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit : 9d598a5e1eee26df95b3910e3f2934890d062caa python : 3.9.1.final.0 python-bits : 64 OS : Linux OS-release : 4.19.121-linuxkit Version : #1 SMP Tue Dec 1 17:50:32 UTC 2020 machine : x86_64 processor : byteorder : little LC_ALL : None LANG : C.UTF-8 LOCALE : en_US.UTF-8 pandas : 1.2.1 numpy : 1.19.5 pytz : 2020.5 dateutil : 2.8.1 pip : 21.0 setuptools : 52.0.0 Cython : None pytest : None hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : None jinja2 : None IPython : None pandas_datareader: None bs4 : None bottleneck : None fsspec : None fastparquet : None gcsfs : None matplotlib : None numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : None pyxlsb : None s3fs : None scipy : None sqlalchemy : None tables : None tabulate : None xarray : None xlrd : None xlwt : None numba : None

Comment From: phofl

This was fixed recently