title: Normalising pandas data frame using StandardScaler() excluding a particular column
body: <p>So I have a data frame which I formed by merging training (labeled) and test (unlabelled) data frames. And to un-append the test data frame I have kept a column which has a identifier if the row belonged to training or test.
  Now I have to normalize all the values in all the columns except for this one column "Sl No." but I am not finding any way to pass this one column.
  Here's what I was doing</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  from sklearn.preprocessing import StandardScaler
  
  data_norm = data_x_filled.copy() #Has training + test data frames combined to form single data frame
  normalizer = StandardScaler()
  data_array = normalizer.fit_transform(data_norm)
  data_norm = pd.DataFrame(data_array,columns = data_norm.columns).set_index(data_norm.index)
  </code></pre>
  
  <p>I just want to exclude the column "Sl No." for normalization but want to retain it after normalization.</p>