BUG: df.plot(kind='barh') does not show xlabel

[McToel]

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

import pandas as pd
import matplotlib.pyplot as plt

co2 = pd.Series({
    'train': 4.8,
    'car': 128.5,
    'aiplane': 98.5
})

co2.plot(
    kind='barh',
    title='CO₂ Tübingen to Berlin',
    xlabel='kg CO₂-eq'
)

plt.show()

Issue Description

The code produces the following plot, with the xlabel showing up on the y-axis.

When only supplying the ylabel, everything works as expected.
When supplying both, the xlabel overrides the ylabel

Expected Behavior

The xlabel should show up on the x-axis.

Installed Versions

INSTALLED VERSIONS

commit : 06d2301
python : 3.9.10.final.0
python-bits : 64
OS : Linux
OS-release : 5.13.0-30-generic
Version : #33~20.04.1-Ubuntu SMP Mon Feb 7 14:25:10 UTC 2022
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.4.1
numpy : 1.22.0
pytz : 2020.1
dateutil : 2.8.1
pip : 22.0.3
setuptools : 58.1.0
Cython : 0.29.21
pytest : 6.2.5
hypothesis : None
sphinx : 3.4.3
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.6.2
html5lib : None
pymysql : None
psycopg2 : 2.8.6
jinja2 : 2.11.2
IPython : 7.19.0
pandas_datareader: None
bs4 : None
bottleneck : None
fastparquet : None
fsspec : 0.8.4
gcsfs : None
matplotlib : 3.5.1
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 6.0.1
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.7.3
sqlalchemy : 1.3.24
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None

[iansheng]

As described in official doc:

xlabel: label, optional
Name to use for the xlabel on x-axis. Default uses index name as xlabel, or the x-column name for planar plots.
ylabel: label, optional
Name to use for the ylabel on y-axis. Default will show no ylabel, or the y-column name for planar plots.

It seems that the default rule of Dataframe.plot takes precedence, causing xlabel not to be displayed.
IMO, these parameters should be consistent with using plt directly.

There is a way to temporarily solve this problem by using the plt library directly.

co2.plot.barh()
plt.title('CO₂ Tübingen to Berlin')
plt.xlabel('kg CO₂-eq')
plt.show()

The xlabel will show up on the x-axis.

[McToel]

The pie plot has a similar issue that might be related. When not Setting ylabel the plot will show None as ylabel

co2.plot(kind='pie')

[iansheng]

Hi! I tried this example in the main branch and found that the xlabel issue has been fixed. Pls check PR 45145, which sloves ur xlabel problem.
Thus this issue should be closed. As for ur second problem，we'd better check if there have beem similar issues.

[iansheng]

Hi, @McToel !

I find that Pandas plot uses common processing logic: It converts data into DataFrame for subsequent operations, meaning that a Series with name=None will change into DF with columns=["None"]. (By default, the value will changed to 0, because the DF does not support NoneType value in columns.)

That is why None label shows on the pie chart.

pandas/pandas/plotting/_matplotlib/core.py

Lines 458 to 466 in 17dda44

	if isinstance(data, ABCSeries):
	label = self.label
	if label is None and data.name is None:
	label = "None"
	if label is None:
	# We'll end up with columns of [0] instead of [None]
	data = data.to_frame()
	else:
	data = data.to_frame(name=label)

I tried to solve the None label problem by dealing with Series and DataFrame separately, and it worked. And 164 testcases became failed :-C. Obviously, modifying the common logic has a big impact.

I'll keep working on it, but before that, I wonder if dealing with Series and DataFrame separately is a step backwards.

[McToel]

I would suggest to just replace "None" with "" which should work according to my quick and dirty test I did (I have no pandas dev setup on my laptop right now and also not much time).