以下是 pandas 数据框和由此生成的条形图:
colors_list = ['#5cb85c','#5bc0de','#d9534f']result.plot(kind='bar',figsize=(15,4),width = 0.8,color = colors_list,edgecolor=None)plt.legend(labels=result.columns,fontsize=14)plt.title("受访者对数据科学领域感兴趣的百分比",fontsize= 16)plt.xticks(字体大小=14)对于 plt.gca().spines.values() 中的脊椎:脊柱.set_visible(假)plt.yticks([])
我需要在相应栏上方显示各个主题的每个兴趣类别的百分比.我可以创建一个包含百分比的列表,但我不明白如何将它添加到相应栏的顶部.
尝试将以下 for
循环添加到您的代码中:
ax = result.plot(kind='bar', figsize=(15,4), width=0.8, color=colors_list, edgecolor=None)对于 ax.patches 中的 p:宽度 = p.get_width()高度 = p.get_height()x, y = p.get_xy()ax.annotate(f'{height}', (x + width/2, y + height*1.02), ha='center')
通常,您使用
The following are the pandas dataframe and the bar chart generated from it:
colors_list = ['#5cb85c','#5bc0de','#d9534f']
result.plot(kind='bar',figsize=(15,4),width = 0.8,color = colors_list,edgecolor=None)
plt.legend(labels=result.columns,fontsize= 14)
plt.title("Percentage of Respondents' Interest in Data Science Areas",fontsize= 16)
plt.xticks(fontsize=14)
for spine in plt.gca().spines.values():
spine.set_visible(False)
plt.yticks([])
I need to display the percentages of each interest category for the respective subject above their corresponding bar. I can create a list with the percentages, but I don't understand how to add it on top of the corresponding bar.
Try adding the following for
loop to your code:
ax = result.plot(kind='bar', figsize=(15,4), width=0.8, color=colors_list, edgecolor=None)
for p in ax.patches:
width = p.get_width()
height = p.get_height()
x, y = p.get_xy()
ax.annotate(f'{height}', (x + width/2, y + height*1.02), ha='center')
In general, you use Axes.annotate
to add annotations to your plots.
This method takes the text
value of the annotation and the xy
coords on which to place the annotation.
In a barplot, each "bar" is represented by a patch.Rectangle
and each of these rectangles has the attributes width
, height
and the xy
coords of the lower left corner of the rectangle, all of which can be obtained with the methods patch.get_width
, patch.get_height
and patch.get_xy
respectively.
Putting this all together, the solution is to loop through each patch in your Axes
, and set the annotation text to be the height
of that patch, with an appropriate xy
position that's just above the centre of the patch - calculated from it's height, width and xy coords.
For your specific need to annotate with the percentages, I would first normalize your DataFrame
and plot that instead.
colors_list = ['#5cb85c','#5bc0de','#d9534f']
# Normalize result
result_pct = result.div(result.sum(1), axis=0)
ax = result_pct.plot(kind='bar',figsize=(15,4),width = 0.8,color = colors_list,edgecolor=None)
plt.legend(labels=result.columns,fontsize= 14)
plt.title("Percentage of Respondents' Interest in Data Science Areas",fontsize= 16)
plt.xticks(fontsize=14)
for spine in plt.gca().spines.values():
spine.set_visible(False)
plt.yticks([])
# Add this loop to add the annotations
for p in ax.patches:
width = p.get_width()
height = p.get_height()
x, y = p.get_xy()
ax.annotate(f'{height:.0%}', (x + width/2, y + height*1.02), ha='center')
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