Pandas plot: using datafram columns as two-levels x-axis Minor and major tick-lables-CodePudding

This is the data and code I use to generate the bar-chart below:

import pandas as pd
import matplotlib.pyplot as plt

data = [["2019","Jan.", 2000,2200,-200],
        ["2019","Feb.", 1500,1400,100],
        ["2019","Dec.", 1200,1100,100],
        ["2020","Jan.", 1400,1300,100],
        ["2020","Dec.", 1300,1200,100]]

df = pd.DataFrame(data, columns=["Year", "Month", "incomes", "expenses", "Balance"])
df.plot.bar()
plt.show()

I would like however to use df["Year"] as the major tick-label and df["Month"] as the minor one, rather than the ordinal number.

How is that done?

CodePudding user response：

You could create labels by iterating through the dataframe, creating strings by concatenating the year and the month.

import pandas as pd
import matplotlib.pyplot as plt

data = [["2019", "Jan.", 2000, 2200, -200],
        ["2019", "Feb.", 1500, 1400, 100],
        ["2019", "Dec.", 1200, 1100, 100],
        ["2020", "Jan.", 1400, 1300, 100],
        ["2020", "Dec.", 1300, 1200, 100]]
df = pd.DataFrame(data, columns=["Year", "Month", "incomes", "expenses", "Balance"])
ax = df.plot.bar()
ax.set_xticks(range(len(df)))
ax.set_xticklabels([f"{month}\n{year}" for year, month in zip(df["Year"], df["Month"])], rotation=0)
plt.show()