This questions relates to a similar question which can be found here: How to create a variability plot with a multi-level grouped label x-axis I have stolen code from this post to get myself started: Plot both multi-index labels on x-axis in pandas plot ...but I am currently stuck my data is in this format: import pandas as pd import numpy as np import matplotlib.pyplot as plt # for same set of random variates np.random.seed(seed = 123) dates = pd.date_range(start = "28/05/2024", end = "28/05/2025", freq = "D") vehicles = np.random.choice(["A", "B", "C", "D", "E", "F"], size = len(dates)) kilometres = np.random.normal(loc = 170, scale = 76, size = len(dates)).round(2) df = pd.DataFrame({"date":dates, "fleet no":vehicles, "kilometres":kilometres}) # groupby to get data into appropriate format df = df.groupby(by = [df["date"].dt.to_period("M"), "fleet no"]).agg({"date":"count", "kilometres":"sum"})\ .rename(columns = {"date":"days"}).reset_index(level = None) I want to be able to produce a graph whereby the x-axis is grouped by both date and fleet no, the same way they are formatted in the subplots produced by this code: groups = df.groupby(by = "date") figure, axes = plt.subplots(nrows = 1, ncols = len(groups), sharey = True, figsize = (16, 5)) for ax, (year, group) in zip(axes, groups): group.set_index("fleet no").rename_axis(year)["days"].plot(kind = "bar", ax = ax) except it should be all in one plot Additionally, the year-month axis labels should be formatted in the "%Y-%b" format. any help would be greatly appreciated Continue reading...
