在条形图上使用 yerr() 绘制标准误差 (std/sqrt(N))

Question

I'm pretty new to Python. I'm trying to plot a box plot for a sample data

I'm trying to plot box plots of mean value of the shared data. I got that part of the code. I'm also trying to plot standard error values on this box plot using yerr() .

My code :

data3=pd.read_csv('demo1.csv')
names=['brow', 'harr', 'hage', 'buch', 'mcre']
d=[data3['brow'].mean(),data3['harr'].mean(),data3['hage'].mean(),data3['buch'].mean(),data3['mcre'].mean()]
N=len(data3['co'])
l=math.sqrt(N)
k=[(data3['brow'].std())/l,(data3['harr'].std())/l,(data3['hage'].std())/l,(data3['buch'].std())/l,(data3['mcre'].std())/l,(data3['phil'].std())/l,(data3['moor'].std())/l]
fig, ax = plt.subplots()
plt.bar(names,d)
plt.bar(len(names),d,yerr=k,align='center',alpha=0.5,ecolor='black',capsize=10)

Im getting an image such as this

But I want the black lines to be against each bar graph and not as a new bar in the plot with all of them together. How can I change this. Am I using the plt the wrong way? Please help.

Answer 1

I don't understand what you were trying to do with your second call to plt.bar()

import math
names=['brow', 'harr', 'hage', 'buch', 'mcre']

data3 = pd.DataFrame({n: np.random.normal(loc=np.random.randint(5,10), scale=np.random.randint(1,10), size=(100,)) for n in names})


d=data3[names].mean()
N=100
l=math.sqrt(N)
k=data3[names].std()/l
fig, ax = plt.subplots()
plt.bar(names,d,yerr=k,align='center',alpha=0.5,ecolor='black',capsize=10)