Correlating weather and stocks with pandas

We will try to correlate stock market data for the Netherlands with the DataFrame we produced last time from the KNMI De Bilt weather data. As a proxy for the stock market, we will use closing prices of the EWN ETF. This might not be the best choice, by the way, so if you have a better idea, please use the appropriate stock ticker. The steps for this exercise are provided as follows:

1. Download the EWN data from Yahoo Finance, with a special function. The code is as follows:

   #EWN start Mar 22, 1996
   start = dt(1996, 3, 22)
   end = dt(2013, 5, 4)
   
   symbol = "EWN"
   quotes = finance.quotes_historical_yahoo(symbol, start, end, asobject=True)

2. Create a DataFrame object with the available dates in the downloaded data:

   df2 = pd.DataFrame(quotes.close, index=dt_idx, columns=[symbol])

3. Join the new DataFrame object with DataFrame of the weather data. We will then obtain the correlation matrix:

   df3 = df.join(df2)
   
   print df3.corr()

   The correlation matrix is as follows:

   

As...