title: Updating one dataframe with the most recent data from a separate dataframe
body: <p>I am trying to update a dataframe of positions with the prices stored in a separate data frames. I would like to put the most recent price in the column "last_price" and the data of that price in column "last_date".</p>
  
  <pre><code>import datetime
  from scipy import stats
  import numpy as np
  import pandas as pd
  
  
  df_portfolio = pd.DataFrame({ 'amount' : np.random.randint(low=0, high=10,     size=(4)),
                      'timestamp' : pd.Timestamp('20130102'),
                      'exch' : pd.Categorical(["e1","e1","e2","e2"]),
                      'token' : pd.Categorical(["BTC","ETH","ETH","LTC"])
                 })
  
  df_ETH_price = pd.DataFrame({
      'date': ('2018-08-11','2018-08-12','2018-08-13'),
      'price' : (322.11,319.57,286.50)    
      })
  
  df_portfolio['last_price'] = np.nan
  df_portfolio['last_date'] = "?"
  
  print(df_portfolio)
  print (df_ETH_price)
  </code></pre>
  
  <p>The expected results would be as follows:</p>
  
  <pre><code>   amount exch  timestamp token  last_price last_date
  0       7   e1 2013-01-02   BTC         NaN         ?
  1       4   e1 2013-01-02   ETH         286.50      2018-08-13
  2       2   e2 2013-01-02   ETH         286.50      2018-08-13
  3       9   e2 2013-01-02   LTC         NaN         ?
  </code></pre>