注意
前往結尾以下載完整的範例程式碼。
作為水平長條圖的離散分佈#
堆疊長條圖可用於視覺化離散分佈。
此範例視覺化了一項調查的結果，其中人們可以對五個元素的量表上的問題給予同意度評級。
水平堆疊是透過為每個類別呼叫 barh() 並將起點作為已繪製長條圖的累積總和透過參數 left 傳遞來實現的。
import matplotlib.pyplot as plt
import numpy as np
category_names = ['Strongly disagree', 'Disagree',
'Neither agree nor disagree', 'Agree', 'Strongly agree']
results = {
'Question 1': [10, 15, 17, 32, 26],
'Question 2': [26, 22, 29, 10, 13],
'Question 3': [35, 37, 7, 2, 19],
'Question 4': [32, 11, 9, 15, 33],
'Question 5': [21, 29, 5, 5, 40],
'Question 6': [8, 19, 5, 30, 38]
}
def survey(results, category_names):
"""
Parameters
----------
results : dict
A mapping from question labels to a list of answers per category.
It is assumed all lists contain the same number of entries and that
it matches the length of *category_names*.
category_names : list of str
The category labels.
"""
labels = list(results.keys())
data = np.array(list(results.values()))
data_cum = data.cumsum(axis=1)
category_colors = plt.colormaps['RdYlGn'](
np.linspace(0.15, 0.85, data.shape[1]))
fig, ax = plt.subplots(figsize=(9.2, 5))
ax.invert_yaxis()
ax.xaxis.set_visible(False)
ax.set_xlim(0, np.sum(data, axis=1).max())
for i, (colname, color) in enumerate(zip(category_names, category_colors)):
widths = data[:, i]
starts = data_cum[:, i] - widths
rects = ax.barh(labels, widths, left=starts, height=0.5,
label=colname, color=color)
r, g, b, _ = color
text_color = 'white' if r * g * b < 0.5 else 'darkgrey'
ax.bar_label(rects, label_type='center', color=text_color)
ax.legend(ncols=len(category_names), bbox_to_anchor=(0, 1),
loc='lower left', fontsize='small')
return fig, ax
survey(results, category_names)
plt.show()
參考資料
此範例中顯示了以下函式、方法、類別和模組的使用
腳本的總執行時間： (0 分鐘 1.218 秒)