如何在Python中的直方圖中顯示百分比標籤

Question

我設法創建一個圖表，顯示我的Pandas數據框中每個年齡段的每個類標籤的記錄數。但我還想看看每個年齡段的「非功能性」課程的百分比標籤。

爲圖形

的Python代碼是

train['age_wpt'] = train.date_recorded.str.split('-').str.get(0).apply(int) - train.construction_year 

figure = plt.figure(figsize=(15,8)) 
plt.hist([ 
     train[(train.status_group=='functional') & (train.age_wpt < 60.0) & (train.age_wpt >= 0.0)]['age_wpt'], 
     train[(train.status_group=='non functional') & (train.age_wpt < 60.0) & (train.age_wpt >= 0.0)]['age_wpt'], 
     train[(train.status_group=='functional needs repair') & (train.age_wpt < 60.0) & (train.age_wpt >= 0.0)]['age_wpt'] 
     ], 
     stacked=True, color = ['b','r','y'], 
     bins = 30,label = ['functional','non functional', 'functional needs repair']) 
plt.xlabel('Age') 
plt.ylabel('Number of records') 
plt.legend() 

這導致下面的圖

Answer 1

範：布爾，可選 如果True，返回的元組的第一個元素將 是歸一化以形成概率密度的計數，即， n/(len(x)`dbin)，即，直方圖的積分將總和 1。如果堆疊也真，直方圖的總和 標準化爲1 默認爲False

plt.hist([ 
     train[(train.status_group=='functional') & (train.age_wpt < 60.0) & (train.age_wpt >= 0.0)]['age_wpt'], 
     train[(train.status_group=='non functional') & (train.age_wpt < 60.0) & (train.age_wpt >= 0.0)]['age_wpt'], 
     train[(train.status_group=='functional needs repair') & (train.age_wpt < 60.0) & (train.age_wpt >= 0.0)]['age_wpt'] 
     ], 
     stacked=False, color = ['b','r','y'], normed=True 
     bins = 30,label = ['functional','non functional', 'functional needs repair'])