Seaborn catplot results in error by changing hue

Question

I have a dataset that looks like this:

	feature_1	feature_2	feature_3	feature_4	feature_5	feature_6	feature_7	feature_8
0	-0.0020185900105266514	-0.004525512052716703	0.004290147446159787	0.008121342033951665	0.019995812082180105	0.02034942055088337	-0.02236798581774497	-0.018665971326321824
1	0.008327938744324304	0.0057161731520134415	0.015149000101932132	0.014244686228342962	0.031266799783999905	0.02556201262830425	0.00491191281881069	0.002627771331087464
2	0.0056570911367399175	0.006780099460379361	-0.0038521559525533412	-0.0042372049750104175	0.025755417055772233	0.029050369619095566	-0.0016924684746490136	0.001915807620861465
3	-0.0066361424845156666	-0.006829267976941566	0.008195242107994306	0.00993842145208005	0.02794638215808405	0.025168342480038512	-0.013222987355723491	-0.011178407242310215
4	0.005111817323414786	0.002367954071875622	-0.0013140356150100757	-0.0027816139194379794	0.025028881734832177	0.029704777330334546	0.0073461329985677545	0.008414726948742138

I have been able to create a catplot that is almost perfect, like this:

sns.catplot(data=test_df, palette="dark", orient="h")

Resulting in:

However, I want the colors to change depending on the results of a list (which I could append to test_df). The list is as follows: classifications = ["class_1", "class_2", "class_1", "class_1", "class_2"]. Ideally, I'd like for the colors of the points to be different depending on the class.

Trying to add the hue parameter errors out, resulting in ValueError: Cannot use 'hue' without 'x' and 'y'

How can I change the colors of the points based on the values of the classifications list?

Answer 1

You can add the class column and melt() into seaborn's preferred long form:

test_df["class"] = classifications
melted = test_df.melt("class", value_name="value", var_name="feature")

sns.catplot(data=melted, x="value", y="feature", hue="class", palette="dark", orient="h")