How to plot a scatter FacetGrid from a dataframe with multi-level columns

Question

data = {('Weight', 'Additive', 'Water'): {0: 3, 1: 3, 2: 3, 3: 3, 4: 3},
        ('Weight', 'Additive', 'Grass'): {0: 6.0, 1: 7.0, 2: 6.0, 3: 0, 4: 0},
        ('Weight', 'Filler', 'Flowers'): {0: 1, 1: 2, 2: 3, 3: 4, 4: 5},
        ('Color', '', ''): {0: 15, 1: 18, 2: 21, 3: 35, 4: 40}}
combo = pd.DataFrame(data)

    Weight               Color
  Additive        Filler      
     Water Grass Flowers      
0        3   6.0       1    15
1        3   7.0       2    18
2        3   6.0       3    21
3        3   0.0       4    35
4        3   0.0       5    40

I have a MultiIndex level table in a pandas dataframe called 'combo' and am trying to make a FacetGrid scatterplot. When I try with the code below I get the error: 'Length of order must be same as number of levels (3), got 2'

grid = sns.FacetGrid(combo, col = combo['Weight'])
grid.map(sns.scatterplot, combo['Weight'], combo['Color'])
plt.show()

Answer 1

• Tested in python 3.10, pandas 1.4.2, matplotlib 3.5.1, seaborn 0.11.2
• It is not recommended to directly use sns.FacetGrid. For figure-level scatter and line plots, use sns.relplot.
• See How to flatten a hierarchical index in columns for more options to flatten the multi-level columns.
• The easiest way to plot the data is to flatten the column names, and then convert the dataframe to a long form with pandas.DataFrame.melt.

import seaborn as sns
import pandas as pd

# sample data
data = {('Weight', 'Additive', 'Water'): {0: 3, 1: 3, 2: 3, 3: 3, 4: 3},
        ('Weight', 'Additive', 'Grass'): {0: 6.0, 1: 7.0, 2: 6.0, 3: 0, 4: 0},
        ('Weight', 'Filler', 'Flowers'): {0: 1, 1: 2, 2: 3, 3: 4, 4: 5},
        ('Color', '', ''): {0: 15, 1: 18, 2: 21, 3: 35, 4: 40}}
df = pd.DataFrame(data)

# flatten the column titles and remove two spaces from the 'Color  ' column name
df.columns = df.columns.to_flat_index().str.join(' ').str.replace('  ', '')

# convert the df to a long format to use with seaborn
dfm = df.melt('Color', var_name='Substance', value_name='Weight')

# clean the column values in the Substance column
dfm.Substance = dfm.Substance.str.replace('Weight ', '').str.replace('_', ' ')

# display(dfm)
    Color       Substance  Weight
0      15  Additive Water     3.0
1      18  Additive Water     3.0
2      21  Additive Water     3.0
3      35  Additive Water     3.0
4      40  Additive Water     3.0
5      15  Additive Grass     6.0
6      18  Additive Grass     7.0
7      21  Additive Grass     6.0
8      35  Additive Grass     0.0
9      40  Additive Grass     0.0
10     15  Filler Flowers     1.0
11     18  Filler Flowers     2.0
12     21  Filler Flowers     3.0
13     35  Filler Flowers     4.0
14     40  Filler Flowers     5.0

plot using hue

g = sns.relplot(kind='scatter', data=dfm, x='Weight', y='Color', hue='Substance')

plot using col

g = sns.relplot(kind='scatter', data=dfm, x='Weight', y='Color', col='Substance')