I have an error with pandas rolling when using floats close to infinity. I display an example here:
import pandas as pd
series = pd.Series(1.,index = pd.date_range('2015-01-01', periods=6))
series[series.index[2]] = 1e19
series
2015-01-01 1.000000e+00
2015-01-02 1.000000e+00
2015-01-03 1.000000e+19
2015-01-04 1.000000e+00
2015-01-05 1.000000e+00
2015-01-06 1.000000e+00
Freq: D, dtype: float64
series.rolling('2D', closed = 'left').mean()
2015-01-01 NaN
2015-01-02 1.000000e+00
2015-01-03 1.000000e+00
2015-01-04 5.000000e+18
2015-01-05 5.000000e+18
2015-01-06 5.000000e-01
Freq: D, dtype: float64
The answer in the last bit should be 1! but it is 0.5. Why does rolling go nuts when using big numbers? same example with smaller float:
series[series.index[2]] = 1e9
series.rolling('2D', closed = 'left').mean()
2015-01-01 NaN
2015-01-02 1.0
2015-01-03 1.0
2015-01-04 500000000.5
2015-01-05 500000000.5
2015-01-06 1.0
Freq: D, dtype: float64
The problem is not with pandas. I tried the same thing in R with rollmean function and it gives the exact same result as pandas. It does not work for value of 1e16 and above. I thing it has to do with how the system handles float.
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