如何在Python中绘制水平条形图的百分比标签？

Question

有人可以帮我绘制x轴标签的百分比给我的水平条形图的以下代码吗？

发现很难找到，因为我想要一个没有x轴标签和刻度的更简单的图表。

[水平条形图][1]

# Plot the figure size
plt.figure(figsize= (8,6))

# New variable and plot the question of the data frame in a normalized in a horizontal bar chat. 
ax1 = df[q1].value_counts(normalize=True).sort_values().plot(kind="barh", color='#fd6a02', width=0.75, zorder=2)

# Draw vague vertical axis lines and set lines to the back of the order
vals = ax1.get_xticks()
for tick in vals:
    ax1.axvline(x=tick, linestyle='dashed', alpha=0.4, color = '#d3d3d3', zorder=1)
    
# Tot3als to produce a composition ratio
total_percent = df[q1].value_counts(normalize=True) *100

# Remove borders
ax1.spines['right'].set_visible(False)
ax1.spines['top'].set_visible(False)
ax1.spines['left'].set_visible(False)
ax1.spines['bottom'].set_visible(False)

# Set the title of the graph inline with the Y axis labels. 
ax1.set_title(q1, weight='bold', size=14, loc = 'left', pad=20, x = -0.16)
             
# ax.text(x,y,text,color)
for i,val in enumerate(total):
    ax1.text(val - 1.5, i, str("{:.2%}".format(total_percent), color="w", fontsize=10, zorder=3)

# Create axis labels
plt.xlabel("Ratio of Responses", labelpad=20, weight='bold', size=12)

每次我得到一个EOF错误。有人能帮忙吗？

Answer 1

它不是基于您的代码，但我会从官方参考中自定义答案。该点是通过 ax.text（） 实现的，这是一个循环过程。

import matplotlib.pyplot as plt
import numpy as np

# Fixing random state for reproducibility
np.random.seed(19680801)

plt.rcdefaults()
fig, ax = plt.subplots()

# Example data
people = ('Tom', 'Dick', 'Harry', 'Slim', 'Jim')
y_pos = np.arange(len(people))
performance = 3 + 10 * np.random.rand(len(people))

ax.barh(y_pos, performance,  align='center')
ax.set_yticks(y_pos)
ax.set_yticklabels(people)
ax.invert_yaxis()  # labels read top-to-bottom
ax.set_xlabel('Performance')
ax.set_title('How fast do you want to go today?')

# Totals to produce a composition ratio
total = sum(performance)

# ax.text(x,y,text,color)
for i,val in enumerate(performance):
    ax.text(val - 1.5, i, str("{:.2%}".format(val/total)), color="w", fontsize=10)

plt.show()