BUG: Plotting bug in Pandas 2.2.2 and 2.2.3

[jlchang]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

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

Reproducible Example

wget https://github.com/jlchang/cb-python-intro-lesson-template/raw/refs/heads/main/episodes/files/data.zip
unzip data.zip

import pandas as pd
df_long = pd.read_pickle('data/df_long.pkl')
albany = df_long[df_long['branch'] == 'Albany Park']
albany.plot()

Issue Description

FYI, Pandas 2.2.2 seems to have a plotting bug (this does not seem to be specific to Colab). For this tutorial, running albany['circulation'].plot() renders:

Expected Behavior

The expected plot looks like:

Pandas 2.0.3 generates the expected plot (Pandas 2.2.3 is also problematic)

Installed Versions

Python 3.10.9 on Mac M1 Max running Sonoma 14.6.1 (23G93)

pd.show_versions()

INSTALLED VERSIONS

commit : 0691c5c
python : 3.10.9
python-bits : 64
OS : Darwin
OS-release : 23.6.0
Version : Darwin Kernel Version 23.6.0: Mon Jul 29 21:14:30 PDT 2024; root:xnu-10063.141.2~1/RELEASE_ARM64_T6000
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 2.2.3
numpy : 1.23.5
pytz : 2022.7.1
dateutil : 2.8.2
pip : 24.0
Cython : None
sphinx : None
IPython : 8.11.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.11.2
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
html5lib : None
hypothesis : None
gcsfs : None
jinja2 : 3.1.2
lxml.etree : None
matplotlib : 3.6.3
numba : 0.56.4
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : None
pyreadstat : None
pytest : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.10.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
tzdata : 2024.2
qtpy : N/A
pyqt5 : None

The same issue happens in Google Colab which is running Python 3.10.12

INSTALLED VERSIONS ------------------ commit : 0691c5c python : 3.10.12 python-bits : 64 OS : Linux OS-release : 6.1.85+ Version : #1 SMP PREEMPT_DYNAMIC Thu Jun 27 21:05:47 UTC 2024 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : en_US.UTF-8 LANG : en_US.UTF-8 LOCALE : en_US.UTF-8

pandas : 2.2.3
numpy : 1.26.4
pytz : 2024.2
dateutil : 2.8.2
pip : 24.1.2
Cython : 3.0.11
sphinx : 5.0.2
IPython : 7.34.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
blosc : None
bottleneck : 1.4.0
dataframe-api-compat : None
fastparquet : None
fsspec : 2024.6.1
html5lib : 1.1
hypothesis : None
gcsfs : 2024.6.1
jinja2 : 3.1.4
lxml.etree : 4.9.4
matplotlib : 3.7.1
numba : 0.60.0
numexpr : 2.10.1
odfpy : None
openpyxl : 3.1.5
pandas_gbq : 0.23.2
psycopg2 : 2.9.9
pymysql : None
pyarrow : 16.1.0
pyreadstat : None
pytest : 7.4.4
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.13.1
sqlalchemy : 2.0.35
tables : 3.8.0
tabulate : 0.9.0
xarray : 2024.9.0
xlrd : 2.0.1
xlsxwriter : None
zstandard : None
tzdata : 2024.2
qtpy : None
pyqt5 : None

[asishm]

Thanks for the report, confirmed in main.

as a workaround, you can run albany['circulation'].sort_index().plot() to get the desired output.

Seems to stem from #55906 where the sorting of the index was removed.

cc @jbrockmendel

[asishm]

simpler reproducer: (slightly modifed the test at pandas/tests/plotting/frame/test_frame.py:test_unordered_ts

from datetime import date
import pandas as pd
import numpy as np

index = [date(2012, 10, 1), date(2012, 8, 1), date(2012, 9, 1)]
values = [3.0, 2.0, 1.0]
df = pd.DataFrame(
    np.array(values),
    index=index,
    columns=["test"],
)

df.plot()

v2.0.3

main

[jlchang]

Thank you for the workaround. And thank you to the pandas team for an incredible library. It is a vital to my daily work.

[rhshadrach]

Thanks for the report. While this likely should have been in the whatsnew, I think the current behavior is more desirable. pandas is now plotting the points in the order of your data, which could be useful in certain cases. Calling sort_index on your data seems to me to be low effort.

[jlchang]

That sounds reasonable. Thanks for explaining the logic behind the change in behavior.