BUG: Inconsistent plotting behaviour.

[maddytae]

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

Reproducible Example

import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns

mpg = sns.load_dataset("mpg")
tips = sns.load_dataset("tips")



# Plot 1: mpg data
fig, ax = plt.subplots(figsize=(3,3))
ax2 = ax.twinx()

k = mpg.pivot_table(index='model_year', columns='cylinders', values='mpg', aggfunc='sum', dropna=True)
k.plot(ax=ax, kind='bar')

k = k.fillna(10) 
k.plot(ax=ax2, kind='line')

plt.show() 

# Plot 2: tips data
fig, ax = plt.subplots(figsize=(3,3))
ax2 = ax.twinx()

k = tips.pivot_table(index='size', columns='smoker', values='total_bill', aggfunc='sum', dropna=True)
k.plot(ax=ax, kind='bar')

k = k.fillna(10)  
k.plot(ax=ax2, kind='line')

plt.show()

Issue Description

I am trying to plot bar chart in primary axis and line chart in secondary axis. The plotting works fine for tips dataset but not for mpg dataset.

Expected Behavior

I should see both bar chart and line chart irrespective of underlying data source.

Installed Versions

INSTALLED VERSIONS

commit : a671b5a
python : 3.9.6.final.0
python-bits : 64
OS : Darwin
OS-release : 23.5.0
Version : Darwin Kernel Version 23.5.0: Wed May 1 20:19:05 PDT 2024; root:xnu-10063.121.3~5/RELEASE_ARM64_T8112
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_CA.UTF-8
LOCALE : en_CA.UTF-8

pandas : 2.1.4
numpy : 1.26.3
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 58.0.4
pip : 21.2.4
Cython : None
pytest : 8.2.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 5.1.1
html5lib : 1.1
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.18.1
pandas_datareader : None
bs4 : 4.12.2
bottleneck : None
dataframe-api-compat: None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.8.2
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 15.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.12.0
sqlalchemy : None
tables : None
tabulate : 0.9.0
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.4
qtpy : 2.4.1
pyqt5 : None

[maddytae]

here is another simplified version for replication.

import matplotlib.pyplot as plt
import pandas as pd

# Create the data as a DataFrame
data = {
    'model_year': [70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82],
    3: [10.0, 10.0, 19.0, 18.0, 10.0, 10.0, 10.0, 21.5, 10.0, 10.0, 23.7, 10.0, 10.0],
    4: [177.0, 357.0, 328.0, 250.0, 417.0, 303.0, 401.5, 407.5, 502.8, 378.3, 865.3, 689.1, 898.0],
    5: [10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 20.3, 25.4, 36.4, 10.0, 10.0],
    6: [82.0, 144.0, 10.0, 152.0, 125.0, 211.0, 200.0, 97.5, 228.8, 137.7, 51.8, 164.0, 85.0],
    8: [254.0, 94.0, 177.0, 264.0, 71.0, 94.0, 132.0, 128.0, 114.3, 186.3, 10.0, 26.6, 10.0]
}

df = pd.DataFrame(data).set_index('model_year')

# Plot 1: mpg data
fig, ax = plt.subplots(figsize=(10, 6))  
ax2 = ax.twinx()



# Plot line chart on secondary axis
df.plot(kind='bar', ax=ax, legend=False, stacked=True)
df.plot(kind='line', ax=ax2, legend=False,linewidth=2)


# Show plot
plt.show()

[maddytae]

For this version while both bar and line are plotted but line starts after skipping one extra x-axis value.

import matplotlib.pyplot as plt
import pandas as pd


data = {
    'size': [1, 2, 3, 4, 5, 6],
    'Yes': [1100.65, 1185.08, 338.30, 336.70, 58.61, 0.00],
    'No': [1700.32, 1380.81, 546.25, 722.00, 91.73, 139.32]
}

df = pd.DataFrame(data).set_index('size')

# Plot data
fig, ax = plt.subplots(figsize=(10, 6))
ax2 = ax.twinx()

# Plot stacked bar chart on primary axis
df.plot(kind='bar', stacked=True, ax=ax, legend=False)

# Plot line chart on secondary axis
df.plot(kind='line', ax=ax2,  legend=False,secondary_y=True)

# Show plot
plt.show()