Pandas Inter-row Computing

Question

I have a DataFrame with daily OHLCV data.

I can calculate the range with:

s['Range'] = s['High'] - s['Low'] 

Simple Now I would like to compute a new column, which I named s['OIR'] (OIR = Open-In-Range)

The ['OIR'] column checks if we are open in the range, and this is done by testing if we opened above yesterday's lows and below yesterday's high. I need to refer to the previous lines, and I'm not quite sure how to do this. The returned values ​​will be True / False.

Thanks.

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edit: I am new to StackExchange and Python. Not sure where to drop sample data. Here is an image of a data frame.

http://i47.tinypic.com/142eb2a.png

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Data Examples: Converting a Dictionary to a DataFrame

 {'High': {<Timestamp: 2007-03-02 00:00:00>: 1384.5, <Timestamp: 2007-03-05 00:00:00>: 1373.0}, 'Last': {<Timestamp: 2007-03-02 00:00:00>: 1365.0, <Timestamp: 2007-03-05 00:00:00>: 1351.5}, 'Low': {<Timestamp: 2007-03-02 00:00:00>: 1364.25, <Timestamp: 2007-03-05 00:00:00>: 1350.5}, 'OIR': {<Timestamp: 2007-03-02 00:00:00>: False, <Timestamp: 2007-03-05 00:00:00>: False}, 'Open': {<Timestamp: 2007-03-02 00:00:00>: 1378.5, <Timestamp: 2007-03-05 00:00:00>: 1356.75}, 'Range': {<Timestamp: 2007-03-02 00:00:00>: 20.25, <Timestamp: 2007-03-05 00:00:00>: 22.5}, 'Volume': {<Timestamp: 2007-03-02 00:00:00>: 1706906, <Timestamp: 2007-03-05 00:00:00>: 1984041}} 

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Answer:

 s['OIR'] = ((s['Open'] < s['High'].shift(1)) & (s['Open'] > s['Low'].shift(1))) 

Answer 1

Reference to previous lines is best achieved using the Series.shift() function:

 In [1]: df = DataFrame(randn(10,3),columns=['O','L','H']) In [2]: df Out[2]: OLH 0 0.605412 0.739866 -0.280222 1 -0.707852 0.785651 0.855183 2 -0.087119 0.518924 0.932167 3 -0.913352 0.369825 1.277771 4 0.434593 -2.942903 0.802413 5 0.075669 -0.135914 1.374454 6 1.112062 0.314946 0.882468 7 -0.706078 -0.202243 0.838088 8 -1.668152 0.414585 0.809932 9 1.452937 -0.048245 0.635499 In [3]: df['OIR'] = ((df.L.shift() <= df.O) & (df.O <= df.H.shift())) In [4]: df Out[4]: OLH OIR 0 0.605412 0.739866 -0.280222 False 1 -0.707852 0.785651 0.855183 False 2 -0.087119 0.518924 0.932167 False 3 -0.913352 0.369825 1.277771 False 4 0.434593 -2.942903 0.802413 True 5 0.075669 -0.135914 1.374454 True 6 1.112062 0.314946 0.882468 True 7 -0.706078 -0.202243 0.838088 False 8 -1.668152 0.414585 0.809932 False 9 1.452937 -0.048245 0.635499 False