如何更改 Python 中饼图切片的顺序
How do I change the order of pie chart slices in Python
我想更改饼图中切片的顺序。当前,切片按降序排列。我希望图表的切片按以下顺序排列:
是 > 有时 > 大多数时候 > 否
我正在使用以下代码:
colors = [ '#99f3bd', '#fbaccc','#a8df65', '#ff7b54']
fig, ax = plt.subplots(figsize=(5,15))
ax.set_title('Treatment Group', fontsize=25, fontname="Times New Roman Bold")
ax = df['q6_t'].value_counts(normalize=True).plot.pie(autopct='%1.0f%%', colors = colors)
ax.set_ylabel("")
plt.savefig('q6_t.png', bbox_inches = 'tight', transparent=True)
我很惊讶我没有找到这个可能是常见问题的重复问题。如果您想要饼图中的特定顺序,则必须对由您的值计数生成的 pandas 系列进行排序:
import matplotlib.pyplot as plt
import pandas as pd
#corresponding color-label pairs
colors = ['#99f3bd', '#fbaccc', '#a8df65', '#ff7b54']
labels = ["Yes", "Sometimes", "Most of the times", "No"]
#test data generation
import numpy as np
n=10
np.random.seed(1234)
df=pd.DataFrame({"A": np.random.random(n), "q6_t": np.random.choice(labels, n)})
#print(df)
fig, ax = plt.subplots(figsize=(8, 8))
ax.set_title('Treatment Group', fontsize=25, fontname="Times New Roman Bold")
#reindex(labels) sorts the index of the value counts according to the list labels
ax = df['q6_t'].value_counts(normalize=True).reindex(labels).plot.pie(autopct='%1.0f%%', colors = colors)
ax.set_ylabel("")
plt.show()
示例输出:
我想更改饼图中切片的顺序。当前,切片按降序排列。我希望图表的切片按以下顺序排列: 是 > 有时 > 大多数时候 > 否
我正在使用以下代码:
colors = [ '#99f3bd', '#fbaccc','#a8df65', '#ff7b54']
fig, ax = plt.subplots(figsize=(5,15))
ax.set_title('Treatment Group', fontsize=25, fontname="Times New Roman Bold")
ax = df['q6_t'].value_counts(normalize=True).plot.pie(autopct='%1.0f%%', colors = colors)
ax.set_ylabel("")
plt.savefig('q6_t.png', bbox_inches = 'tight', transparent=True)
我很惊讶我没有找到这个可能是常见问题的重复问题。如果您想要饼图中的特定顺序,则必须对由您的值计数生成的 pandas 系列进行排序:
import matplotlib.pyplot as plt
import pandas as pd
#corresponding color-label pairs
colors = ['#99f3bd', '#fbaccc', '#a8df65', '#ff7b54']
labels = ["Yes", "Sometimes", "Most of the times", "No"]
#test data generation
import numpy as np
n=10
np.random.seed(1234)
df=pd.DataFrame({"A": np.random.random(n), "q6_t": np.random.choice(labels, n)})
#print(df)
fig, ax = plt.subplots(figsize=(8, 8))
ax.set_title('Treatment Group', fontsize=25, fontname="Times New Roman Bold")
#reindex(labels) sorts the index of the value counts according to the list labels
ax = df['q6_t'].value_counts(normalize=True).reindex(labels).plot.pie(autopct='%1.0f%%', colors = colors)
ax.set_ylabel("")
plt.show()
示例输出: