I have a log with some internal counter and time. Here is example:
parrots id MSK
0 16745 0 0 days 14:43:50.570000
1 95782 1 0 days 14:43:50.670000
2 180885 2 0 days 14:43:50.770000
3 255244 3 0 days 14:43:50.870000
4 335638 4 0 days 14:43:50.970000
6 498680 6 0 days 14:43:51.070000
7 575399 7 0 days 14:43:51.170000
8 655763 8 0 days 14:43:51.270000
9 735779 9 0 days 14:43:51.370000
11 895504 11 0 days 14:43:51.470000
12 975212 12 0 days 14:43:51.570000
13 1055381 13 0 days 14:43:51.670000
14 1135338 14 0 days 14:43:51.770000
16 1295328 16 0 days 14:43:51.870000
17 1377079 17 0 days 14:43:51.970000
18 1456391 18 0 days 14:43:52.070000
19 1536884 19 0 days 14:43:52.170000
21 1698646 21 0 days 14:43:52.270000
22 1776530 22 0 days 14:43:52.370000
23 1856670 23 0 days 14:43:52.470000
24 1937150 24 0 days 14:43:52.570000
26 2097155 26 0 days 14:43:52.670000
27 2176568 27 0 days 14:43:52.770000
28 2256633 28 0 days 14:43:52.870000
29 2337062 29 0 days 14:43:52.970000
where 'parrots' is counter and 'MSK' time.
dtype:
parrots int64
id int64
MSK timedelta64[ns]
dtype: object
Next, I use sklearn.linear_model.LinearRegression:
Xsubst = f01_subst_nodup[['MSK']]
ysubst = f01_subst_nodup['parrots']
msk2parrots_subst = skl.LinearRegression()
msk2parrots_subst.fit(Xsubst, ysubst)
output: LinearRegression()
Next, I check result:
ysubst_pred = msk2parrots_subst.predict(Xsubst)
Error output:
TypeError: The DType <class 'numpy.dtype[timedelta64]'> could not be promoted by <class 'numpy.dtype[float64]'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is `object`. The full list of DTypes is: (<class 'numpy.dtype[timedelta64]'>, <class 'numpy.dtype[float64]'>)
What I do wrong?
Try some examples from Stackoverflow and skikit, but nothing help