Grouping boxplots in seaborn when input is a DataFrame

You can use directly boxplot (I imagine when the question was asked, that was not possible, but with seaborn version > 0.6 it is).

As explained by @mwaskom, you have to "melt" the sample dataframe into its "long-form" where each column is a variable and each row is an observation:

df_long = pd.melt(df, "b", var_name="a", value_name="c")

# display(df_long.head())
   b   a   c
0  1  a1   2
1  2  a1   4
2  1  a1   5
3  2  a1  10
4  2  a1   9

Then you just plot it:

sns.boxplot(x="a", hue="b", y="c", data=df_long)

As the other answers note, the boxplot function is limited to plotting a single "layer" of boxplots, and the groupby parameter only has an effect when the input is a Series and you have a second variable you want to use to bin the observations into each box..

However, you can accomplish what I think you're hoping for with the factorplot function, using kind="box". But, you'll first have to "melt" the sample dataframe into what is called long-form or "tidy" format where each column is a variable and each row is an observation:

df_long = pd.melt(df, "b", var_name="a", value_name="c")

Then it's very simple to plot:

sns.factorplot("a", hue="b", y="c", data=df_long, kind="box")