title: Compare PandaS DataFrames and return rows that are missing from the first one
body: <p>I have 2 dataFrames and want to compare them and return rows from the first one (df1) that are not in the second one (df2).  I found a way to compare them and return the differences, but can't figure out how to return only missing ones from df1.</p>
  
  <pre><code>import pandas as pd
  from pandas import Series, DataFrame
  
  df1 = pd.DataFrame( { 
  "City" : ["Chicago", "San Franciso", "Boston"] , 
  "State" : ["Illinois", "California", "Massachusett"] } )
  
  df2 = pd.DataFrame( { 
  "City" : ["Chicago",  "Mmmmiami", "Dallas" , "Omaha"] , 
  "State" : ["Illinois", "Florida", "Texas", "Nebraska"] } )
  
  
  
  df = pd.concat([df1, df2])
  df = df.reset_index(drop=True)
  
  df_gpby = df.groupby(list(df.columns))
  idx = [x[0] for x in df_gpby.groups.values() if len(x) == 1]
  blah = df.reindex(idx)
  </code></pre>