title: Scaling / Normalizing pandas column
body: <p>I have a dataframe like:</p>
  
  <pre><code>TOTAL | Name
  3232     Jane
  382      Jack
  8291     Jones
  </code></pre>
  
  <p>I'd like to create a newly scaled column in the dataframe called <code>SIZE</code> where <code>SIZE</code> is a number between 5 and 50.</p>
  
  <p>For Example:</p>
  
  <pre><code>TOTAL | Name | SIZE
  3232     Jane   24.413
  382      Jack   10
  8291     Jones  50
  </code></pre>
  
  <p>I've tried</p>
  
  <pre><code>from sklearn.preprocessing import MinMaxScaler
  import pandas as pd
  
  scaler=MinMaxScaler(feature_range=(10,50))
  df["SIZE"]=scaler.fit_transform(df["TOTAL"])
  </code></pre>
  
  <p>but got <code>Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.</code></p>
  
  <p>I've tried other things, such as creating a list, transforming it, and appending it back to the dataframe, among other things.</p>
  
  <p>What is the easiest way to do this?</p>
  
  <p>Thanks!</p>