old_contents: #!/usr/bin/python
  
new_contents: #%%
  # Read in data
  import pandas as pd
  import numpy as np
  # Download CSV from https://goo.gl/zJN9rm
  df = pd.read_csv(r'C:/Users/alex/Downloads/interest.csv')
  
  #%%
  # Compute z-scores
  # thanks http://stackoverflow.com/a/24762240
  cols = set(['PA', 'GB%', 'LD%', 'G', 'OPS', 
  'IFFB%', 'BB%', 'AVG', 'wRC+', 'BABIP', 'K%', 
  'wOBA', 'ISO', 'FB%', 'SLG', 'WAR', 'OBP'])
  
  # Z-scores and squared z-scores
  zscore2_cols = []
  for col in cols:
      col_zscore = col + '_zscore'
      colz2 = col + '_zscore2'
      zscore2_cols.append(colz2)
      df[col_zscore] = (df[col] - df[col].mean())/df[col].std(ddof=0)
      df[colz2] = ((df[col] - df[col].mean())/df[col].std(ddof=0))**2
   
  #%%
  # Sum the _zscore2 columns and find the min
  mysum = df.loc[:,zscore2_cols].sum(axis=1)
  
  # Who was the least interesting?
  ixmin = np.argmin(mysum)
  print df.loc[ixmin,['Name']]
  
  # Who was the most interesting?
  ixmax = np.argmax(mysum)
  print df.loc[ixmax,['Name']]
  
  #%%
  # Make the CSV for the histogram
  df['zscore_square_sum'] = mysum
  df2 = df.loc[:,['Name','zscore_square_sum']]
  df2 = df2.sort(['zscore_square_sum'])
  df2.to_csv('histogram.csv',index=False)
  
  #%%
  # Try doing some scatter plots
  import matplotlib.pyplot as plt
  
  stats = ('FB%','wOBA')
  plt.plot(df.loc[:,[stats[0]]],df.loc[:,[stats[1]]],'o')
  plt.plot(df.loc[ixmin,[stats[0]]],df.loc[ixmin,[stats[1]]],'ro')
  plt.xlabel()
  plt.show()
  
  #%%
  # Where was Piscotty the most interesting?
  df3 = df.loc[ixmin,zscore2_cols]
  #df3.to_csv('Piscotty_scores.csv',index=True)
  
subject: Update analysis.py