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If you're not already wedded to your design, I'd recommend looking at <a href="http://pandas.pydata.org/" rel="nofollow">pandas</a>. It makes stuff like this a lot easier than it would otherwise be. Getting the data: <pre><code>>>> from pandas.io.data import DataReader >>> apple = DataReader("AAPL", "yahoo") >>> apple <class 'pandas.core.frame.DataFrame'> DatetimeIndex: 786 entries, 2010-01-04 00:00:00 to 2013-02-15 00:00:00 Data columns: Open 786 non-null values High 786 non-null values Low 786 non-null values Close 786 non-null values Volume 786 non-null values Adj Close 786 non-null values dtypes: float64(5), int64(1) >>> apple[:5] Open High Low Close Volume Adj Close Date 2010-01-04 213.43 214.50 212.38 214.01 17633200 210.90 2010-01-05 214.60 215.59 213.25 214.38 21496600 211.26 2010-01-06 214.38 215.23 210.75 210.97 19720000 207.90 2010-01-07 211.75 212.00 209.05 210.58 17040400 207.52 2010-01-08 210.30 212.00 209.06 211.98 15986100 208.90 </code></pre> Adding a new column: <pre><code>>>> apple["new_column"] = apple["Open"]/apple["Volume"]**0.3 + 5 >>> apple[:5] Open High Low Close Volume Adj Close new_column Date 2010-01-04 213.43 214.50 212.38 214.01 17633200 210.90 6.430066 2010-01-05 214.60 215.59 213.25 214.38 21496600 211.26 6.354936 2010-01-06 214.38 215.23 210.75 210.97 19720000 207.90 6.389032 2010-01-07 211.75 212.00 209.05 210.58 17040400 207.52 6.433440 2010-01-08 210.30 212.00 209.06 211.98 15986100 208.90 6.451164 </code></pre> Choosing only the columns we want: <pre><code>>>> new = apple[["Close", "new_column"]] >>> new[:5] Close new_column Date 2010-01-04 214.01 6.430066 2010-01-05 214.38 6.354936 2010-01-06 210.97 6.389032 2010-01-07 210.58 6.433440 2010-01-08 211.98 6.451164 </code></pre> Et cetera.
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1. USSylvain Defresne
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