title: Unexpected result sklearn StandardScaler
body: <p>I try to test some Scaler with following code.
  I expect a result like the blue distributions but scaled.
  What I get is the orange one.
  Can anybody help me?</p>
  <pre><code>import matplotlib.pyplot as plt
  import numpy as np
  import pandas as pd
  from sklearn.preprocessing import StandardScaler
  
  
  x1=np.random.normal(loc=21,scale=0.2,size=(100,1))
  x2=np.random.normal(loc=1000,scale=550,size=(100,1))
  
  data=np.concatenate((x1,x2),axis=1)
  
  df=pd.DataFrame(data,columns=['x1','x2'])
  
  fig1, axs=plt.subplots(nrows=1, ncols=2)
  axs[0].hist(df['x1'])
  axs[1].hist(df['x2'])
  
  scaler = StandardScaler()
  scaler.fit(df)
  df_trans=scaler.transform(df)
  
  fig2, axs=plt.subplots(nrows=1,ncols=2)
  axs[0].hist(df_trans[0],color='orange')
  axs[1].hist(df_trans[1],color='orange')
  </code></pre>
  <p><a href="https://i.stack.imgur.com/tR5bA.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/tR5bA.png" alt="enter image description here" /></a>
  <a href="https://i.stack.imgur.com/U1FbC.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/U1FbC.png" alt="enter image description here" /></a></p>