après avoir cherché une solution similaire et n'avoir rien trouvé d'assez flexible, j'ai décidé d'écrire ma propre fonction. Il vous permet d'avoir autant de barres par groupe que vous le souhaitez et de spécifier à la fois la largeur d'un groupe ainsi que les largeurs individuelles des barres au sein des groupes.
Prendre plaisir:
from matplotlib import pyplot as plt
def bar_plot(ax, data, colors=None, total_width=0.8, single_width=1, legend=True):
"""Draws a bar plot with multiple bars per data point.
Parameters
----------
ax : matplotlib.pyplot.axis
The axis we want to draw our plot on.
data: dictionary
A dictionary containing the data we want to plot. Keys are the names of the
data, the items is a list of the values.
Example:
data = {
"x":[1,2,3],
"y":[1,2,3],
"z":[1,2,3],
}
colors : array-like, optional
A list of colors which are used for the bars. If None, the colors
will be the standard matplotlib color cyle. (default: None)
total_width : float, optional, default: 0.8
The width of a bar group. 0.8 means that 80% of the x-axis is covered
by bars and 20% will be spaces between the bars.
single_width: float, optional, default: 1
The relative width of a single bar within a group. 1 means the bars
will touch eachother within a group, values less than 1 will make
these bars thinner.
legend: bool, optional, default: True
If this is set to true, a legend will be added to the axis.
"""
if colors is None:
colors = plt.rcParams['axes.prop_cycle'].by_key()['color']
n_bars = len(data)
bar_width = total_width / n_bars
bars = []
for i, (name, values) in enumerate(data.items()):
x_offset = (i - n_bars / 2) * bar_width + bar_width / 2
for x, y in enumerate(values):
bar = ax.bar(x + x_offset, y, width=bar_width * single_width, color=colors[i % len(colors)])
bars.append(bar[0])
if legend:
ax.legend(bars, data.keys())
if __name__ == "__main__":
data = {
"a": [1, 2, 3, 2, 1],
"b": [2, 3, 4, 3, 1],
"c": [3, 2, 1, 4, 2],
"d": [5, 9, 2, 1, 8],
"e": [1, 3, 2, 2, 3],
"f": [4, 3, 1, 1, 4],
}
fig, ax = plt.subplots()
bar_plot(ax, data, total_width=.8, single_width=.9)
plt.show()
Production: