One year of sample data:
import pandas as pd
import numpy.random as rnd
import seaborn as sns
n = 365
df = pd.DataFrame(data = {"A":rnd.randn(n), "B":rnd.randn(n)+1},
index=pd.date_range(start="2017-01-01", periods=n, freq="D"))
I want to boxplot these data side-by-side grouped by the month (i.e., two boxes per month, one for A
and one for B
).
For a single column sns.boxplot(df.index.month, df["A"])
works fine. However, sns.boxplot(df.index.month, df[["A", "B"]])
throws an error (ValueError: cannot copy sequence with size 2 to array axis with dimension 365
). Melting the data by the index (pd.melt(df, id_vars=df.index, value_vars=["A", "B"], var_name="column")
) in order to use seaborn's hue
property as a workaround doesn't work either (TypeError: unhashable type: 'DatetimeIndex'
).
(A solution doesn't necessarily need to use seaborn, if it is easier using plain matplotlib.)
I found a workaround that basically produces what I want. However, it becomes somewhat awkward to work with once the DataFrame includes more variables than I want to plot. So if there is a more elegant/direct way to do it, please share!
df_stacked = df.stack().reset_index()
df_stacked.columns = ["date", "vars", "vals"]
df_stacked.index = df_stacked["date"]
sns.boxplot(x=df_stacked.index.month, y="vals", hue="vars", data=df_stacked)
Produces:
here's a solution using pandas melting and seaborn:
import pandas as pd
import numpy.random as rnd
import seaborn as sns
n = 365
df = pd.DataFrame(data = {"A": rnd.randn(n),
"B": rnd.randn(n)+1,
"C": rnd.randn(n) + 10, # will not be plotted
},
index=pd.date_range(start="2017-01-01", periods=n, freq="D"))
df['month'] = df.index.month
df_plot = df.melt(id_vars='month', value_vars=["A", "B"])
sns.boxplot(x='month', y='value', hue='variable', data=df_plot)
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