问题
I have a data frame with the price of several securities as columns and I can't find a solution to run TA-Lib in one shot because it needs numpy.ndarray.
How can I run TA-Lib over multiple securities and get a data frame in return?
import talib as ta
d = {'security1': [1,2,8,9,8,5], 'security2': [3,8,5,4,3,5]}
df = pd.DataFrame(data=d)
df
Out[518]:
security1 security2
0 1 3
1 2 8
2 8 5
3 9 4
4 8 3
5 5 5
ta.EMA(df, 2)
TypeError: Argument 'real' has incorrect type (expected numpy.ndarray, got DataFrame)
ta.EMA(df['security1'], 2)
Out[520]:
0 NaN
1 1.500000
2 5.833333
3 7.944444
4 7.981481
5 5.993827
dtype: float64
type(df['security1'])
Out[524]: pandas.core.series.Series
When I convert the data frame to a numpy.ndarray it still throws an exception:
ta.EMA(df.values, 2)
Out[528]: Exception: input array type is not double
Thank you.
回答1:
TA-Lib is expecting floating point data, whereas yours is integral.
As such, when constructing your dataframe you need to coerce the input data by specifying dtype=numpy.float64:
import pandas
import numpy
import talib
d = {'security1': [1,2,8,9,8,5], 'security2': [3,8,5,4,3,5]}
df = pandas.DataFrame(data=d, dtype=numpy.float64) # note numpy.float64 here
TA-Lib expects 1D arrays, which means it can operate on pandas.Series but not pandas.DataFrame.
You can, however, use pandas.DataFrame.apply to apply a function on each column of your dataframe
df.apply(lambda c: talib.EMA(c, 2))
security1 security2
0 NaN NaN
1 1.500000 5.500000
2 5.833333 5.166667
3 7.944444 4.388889
4 7.981481 3.462963
5 5.993827 4.487654
来源：https://stackoverflow.com/questions/51712269/how-to-run-ta-lib-on-multiple-columns-of-a-pandas-dataframe