Pandas version checks
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[X] I have checked that this issue has not already been reported.
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[X] I have confirmed this bug exists on the latest version of pandas.
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[ ] I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
df = pd.DataFrame([{"a": 1, "b": 2}, {"a": 10, "b": 20}, {"a": 100, "b": 200}])
df = df.sample(frac = 1, random_state = 0)
print(df) # The data frame is shuffled
print(df.loc[0, 'a']) # But it doesn't print the element from the shuffled version, instead it prints value from the original version of the data frame.
Issue Description
The shuffling in pandas doesn't have an impact when a field value is printed with loc. To reproduce this:
- Take a data frame.
- Shuffle it with
df.sample(). - Assign it to the original data frame.
- Print the data frame (you will get the shuffled version being printed).
- Now, print a single field value with
loc, this will still print according to the original data frame as it was before shuffling.
Expected Behavior
The data frame should found to be modified in all cases.
Installed Versions
python : 3.8.10.final.0
python-bits : 64
OS : Linux
OS-release : 5.10.147+
Version : #1 SMP Sat Dec 10 16:00:40 UTC 2022
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.5.3
numpy : 1.21.6
pytz : 2022.7.1
dateutil : 2.8.2
setuptools : 57.4.0
pip : 22.0.4
Cython : 0.29.33
pytest : 3.6.4
hypothesis : None
sphinx : 3.5.4
blosc : None
feather : 0.4.1
xlsxwriter : None
lxml.etree : 4.9.2
html5lib : 1.0.1
pymysql : None
psycopg2 : 2.9.5
jinja2 : 2.11.3
IPython : 7.9.0
pandas_datareader: 0.9.0
bs4 : 4.6.3
bottleneck : None
brotli : None
fastparquet : None
fsspec : 2023.1.0
gcsfs : None
matplotlib : 3.2.2
numba : 0.56.4
numexpr : 2.8.4
odfpy : None
openpyxl : 3.0.10
pandas_gbq : 0.17.9
pyarrow : 9.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.7.3
snappy : None
sqlalchemy : 1.4.46
tables : 3.7.0
tabulate : 0.8.10
xarray : 2022.12.0
xlrd : 1.2.0
xlwt : 1.3.0
zstandard : None
tzdata : None
Comment From: hafiz031
Not a bug. I should have reset the index:
df = df.sample(frac = 1, random_state = 0).reset_index(drop = True)