I have an OHLC price data set, that I have parsed from CSV into a Pandas dataframe and resampled to 15 min bars:
DatetimeIndex: 500047 entries, 1998-05-04 04:45:00 to 2012-08-07 00:15:00
Close 363152 non-null values
High 363152 non-null values
Low 363152 non-null values
Open 363152 non-null values
I would like to add various calculated columns, starting with simple ones such as period Range (H-L) and then booleans to indicate the occurrence of price patterns that I will define - e.g. a hammer candle pattern, for which a sample definition:
return c > l + (h-1)/2
return lower_wick(o,l,c) >= 2 * real_body(o,c)
return lower_wick_at_least_twice_real_body(row["Open"],row["Low"],row["Close"]) \
Basic problem: how do I map the function to the column, specifically where I would like to reference more than one other column or the whole row or whatever?
This post deals with adding two calculated columns off of a single source column, which is close, but not quite it.
And slightly more advanced: for price patterns that are determined with reference to more than a single bar (T), how can I reference different rows (e.g. T-1, T-2 etc.) from within the function definition?
Many thanks in advance.