BUG: astype() on an integer DataFrame changes the order of data (original) (raw)
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Code Sample, a copy-pastable example
import numpy as np import pandas as pd npa = np.random.RandomState(0).randint(1000, size=(20, 8)) df = pd.DataFrame(npa, columns=[f'c{i}' for i in range(8)]) print(df.iloc[:6, :3])
c0 c1 c2
0 684 559 629
1 9 723 277
2 600 396 314
3 600 849 677
4 115 976 755
5 99 984 177
print(df.iloc[:6, :3].astype('int32'))
c0 c1 c2
0 684 600 115
1 559 396 976
2 629 314 755
3 9 600 99
4 723 849 984
5 277 677 177
Problem description
The order of output result is changed unexpectedly after astype is called. It may caused by data continuity as df.iloc[:6, :3].copy().astype('int32') works as expected.
Expected Output
print(df.iloc[:6, :3].astype('int32'))
c0 c1 c2
0 684 559 629
1 9 723 277
2 600 396 314
3 600 849 677
4 115 976 755
5 99 984 177
Output of pd.show_versions()
Details
INSTALLED VERSIONS
commit : f00ed8f
python : 3.8.5.final.0
python-bits : 64
OS : Darwin
OS-release : 19.6.0
Version : Darwin Kernel Version 19.6.0: Thu May 6 00:48:39 PDT 2021; root:xnu-6153.141.33~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : zh_CN.UTF-8
pandas : 1.3.0
numpy : 1.18.5
pytz : 2021.1
dateutil : 2.8.1
pip : 20.2.2
setuptools : 49.6.0.post20200814
Cython : 0.29.23
pytest : 6.2.2
hypothesis : 6.3.0
sphinx : 3.2.1
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 2.11.2
IPython : 7.17.0
pandas_datareader: None
bs4 : None
bottleneck : None
fsspec : None
fastparquet : 0.4.2
gcsfs : None
matplotlib : 3.2.2
numexpr : 2.7.1
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 4.0.0
pyxlsb : None
s3fs : None
scipy : 1.6.0
sqlalchemy : 1.3.18
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
numba : 0.53.0