如何在Python中绘制水平条形图的百分比标签？

如何解决如何在Python中绘制水平条形图的百分比标签？

考虑到以下水平条形图代码，有人可以帮我按百分比绘制x轴标签吗？

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,size=12)

每次我出现EOF错误。有人可以帮忙吗？

解决方法

它不是基于您的代码，但是我将从官方参考中定制答案。 可以通过ax.text()实现这一点，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()