Customizing legend with scatterplot

Question

I struggle with customizing the legend of my scatterplot. Here is a snapshot :

And here is a code sample :

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
sns.set()

my_df = pd.DataFrame([[5, 3, 1], [2, 1, 2], [3, 4, 1], [1, 2, 1]],
                     columns=["DUMMY_CT", "FOO_CT", "CI_CT"])

g = sns.scatterplot("DUMMY_CT", "FOO_CT", data=my_df, size="CI_CT")
g.set_title("Number of Baz", weight="bold")
g.set_xlabel("Dummy count")
g.set_ylabel("Foo count")
g.get_legend().set_title("Baz count")

Also, I work in a Jupyter-lab notebook with Python 3, if it helps.

The red thingy issue

First things first, I wish to hide the name of the CI_CT variable (contoured in red on the picture). After exploring the whole documentation for this afternoon, I found the get_legend_handlers_label method (see here), which produces the following :

>>> g.get_legend_handles_labels()
([<matplotlib.collections.PathCollection at 0xfaaba4a8>,
  <matplotlib.collections.PathCollection at 0xfaa3ff28>,
  <matplotlib.collections.PathCollection at 0xfaa3f6a0>,
  <matplotlib.collections.PathCollection at 0xfaa3fe48>],
  ['CI_CT', '0', '1', '2'])

Where I can spot my dear CI_CT string. However, I'm unable to change this name or to hide it completely. I found a dirty way, that basically consists in not using efficiently the dataframe passed as a data parameter. Here is the scatterplot call :

g = sns.scatterplot("DUMMY_CT", "FOO_CT", data=my_df, size=my_df["CI_CT"].values)

Result here :

It works, but is there a cleaner way to achieve this?

The green thingy issue

Displaying a 0 level in this legend is incorrect, since there is no zero value in the column CI_CT of my_df. It is therefore misleading for the readers, who might assume the smaller dots represents a value of 0 or 1. I wish to setup a defined scale, in the way one can do it for the x and y axis. However, I cannot achieve it. Any idea?

TL;DR : A broader question that could solve everything

Those adventures make me wonder if there is a way to handle the data you can pass to the scatterplots with hue and size parameters in a clean, x-and-y-axis way. Is it actually possible?

Please pardon my English, please let me know if the question is too broad or uncorrectly labelled.

Answer 1

The "green thing issue", namely that there is one more legend entry than there are sizes, is solved by specifying legend="full".

g = sns.scatterplot(..., legend="full")

The "red thing issue" is more tricky. The problem here is that seaborn misuses a normal legend label as a headline for the legend. An option is indeed to supply the values directly instead of the name of the column, to prevent seaborn from using that column name.

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
sns.set()

my_df = pd.DataFrame([[5, 3, 1], [2, 1, 2], [3, 4, 1], [1, 2, 1]],
                     columns=["DUMMY_CT", "FOO_CT", "CI_CT"])

g = sns.scatterplot("DUMMY_CT", "FOO_CT", data=my_df, size=my_df["CI_CT"].values, legend="full")
g.set_title("Number of Baz", weight="bold")
g.set_xlabel("Dummy count")
g.set_ylabel("Foo count")
g.get_legend().set_title("Baz count")

plt.show()

If you really must use the column name itself, a hacky solution is to crawl into the legend and remove the label you don't want.

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
sns.set()

my_df = pd.DataFrame([[5, 3, 1], [2, 1, 2], [3, 4, 1], [1, 2, 1]],
                     columns=["DUMMY_CT", "FOO_CT", "CI_CT"])

g = sns.scatterplot("DUMMY_CT", "FOO_CT", data=my_df, size="CI_CT", legend="full")
g.set_title("Number of Baz", weight="bold")
g.set_xlabel("Dummy count")
g.set_ylabel("Foo count")
g.get_legend().set_title("Baz count")

#Hack to remove the first legend entry (which is the undesired title)
vpacker = g.get_legend()._legend_handle_box.get_children()[0]
vpacker._children = vpacker.get_children()[1:]

plt.show()