<p dir="auto">I have a dataframe that has some column names as integers (e.g., 1, 2, 3, 4, etc.) indicating a number of features used in a machine learning problem. However, as of seaborn version 0.11.0, a TypeError is raised because seaborn never checks for vectors/columns in <code class="notranslate">data</code> if <code class="notranslate">x</code> or <code class="notranslate">y</code> are integers.</p>
<h2 dir="auto">Example</h2>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="import seaborn as sns
import numpy as np
import pandas as pd

data = np.random.randint(5,30,size=(10,2))
df = pd.DataFrame(data, columns=['x', 1])
ax = sns.scatterplot(x='x', y=1, data=df)"><pre class="notranslate"><code class="notranslate">import seaborn as sns
import numpy as np
import pandas as pd

data = np.random.randint(5,30,size=(10,2))
df = pd.DataFrame(data, columns=['x', 1])
ax = sns.scatterplot(x='x', y=1, data=df)
</code></pre></div>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="Traceback (most recent call last):

  File &quot;&lt;ipython-input-91-7086dc4312d0&gt;&quot;, line 1, in &lt;module&gt;
    ax = sns.scatterplot(x='x', y=1, data=df)

  File &quot;C:\Users\nigo0024\Anaconda3\envs\sip_run_2\lib\site-packages\seaborn\_decorators.py&quot;, line 46, in inner_f
    return f(**kwargs)

  File &quot;C:\Users\nigo0024\Anaconda3\envs\sip_run_2\lib\site-packages\seaborn\relational.py&quot;, line 794, in scatterplot
    p = _ScatterPlotter(

  File &quot;C:\Users\nigo0024\Anaconda3\envs\sip_run_2\lib\site-packages\seaborn\relational.py&quot;, line 580, in __init__
    super().__init__(data=data, variables=variables)

  File &quot;C:\Users\nigo0024\Anaconda3\envs\sip_run_2\lib\site-packages\seaborn\_core.py&quot;, line 604, in __init__
    self.assign_variables(data, variables)

  File &quot;C:\Users\nigo0024\Anaconda3\envs\sip_run_2\lib\site-packages\seaborn\_core.py&quot;, line 667, in assign_variables
    plot_data, variables = self._assign_variables_longform(

  File &quot;C:\Users\nigo0024\Anaconda3\envs\sip_run_2\lib\site-packages\seaborn\_core.py&quot;, line 895, in _assign_variables_longform
    if val is not None and len(data) != len(val):

TypeError: object of type 'int' has no len()"><pre class="notranslate"><code class="notranslate">Traceback (most recent call last):

  File "&lt;ipython-input-91-7086dc4312d0&gt;", line 1, in &lt;module&gt;
    ax = sns.scatterplot(x='x', y=1, data=df)

  File "C:\Users\nigo0024\Anaconda3\envs\sip_run_2\lib\site-packages\seaborn\_decorators.py", line 46, in inner_f
    return f(**kwargs)

  File "C:\Users\nigo0024\Anaconda3\envs\sip_run_2\lib\site-packages\seaborn\relational.py", line 794, in scatterplot
    p = _ScatterPlotter(

  File "C:\Users\nigo0024\Anaconda3\envs\sip_run_2\lib\site-packages\seaborn\relational.py", line 580, in __init__
    super().__init__(data=data, variables=variables)

  File "C:\Users\nigo0024\Anaconda3\envs\sip_run_2\lib\site-packages\seaborn\_core.py", line 604, in __init__
    self.assign_variables(data, variables)

  File "C:\Users\nigo0024\Anaconda3\envs\sip_run_2\lib\site-packages\seaborn\_core.py", line 667, in assign_variables
    plot_data, variables = self._assign_variables_longform(

  File "C:\Users\nigo0024\Anaconda3\envs\sip_run_2\lib\site-packages\seaborn\_core.py", line 895, in _assign_variables_longform
    if val is not None and len(data) != len(val):

TypeError: object of type 'int' has no len()
</code></pre></div>
<h2 dir="auto">Version info:</h2>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="sns.__version__
import matplotlib
matplotlib.__version__"><pre class="notranslate"><code class="notranslate">sns.__version__
import matplotlib
matplotlib.__version__
</code></pre></div>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="'0.11.0'
'3.3.3'"><pre class="notranslate"><code class="notranslate">'0.11.0'
'3.3.3'
</code></pre></div>
<p dir="auto">Apologies if this is a naive request or I've missed something in the existing functionality, but I have a situation where I have data for two samples and I'd like to view a quantile-quantile plot to compare the distributions of the two samples. Both scipy and statsmodels have functions to make qq plots, but they both require comparison of data with a distribution, they don't support comparison of data with data.</p>
<p dir="auto">I was wondering if it would make sense to add a "qq" kind to the jointplot() function, which would use the central plot component for the qq plot but still also plot marginal histograms.</p>