Custom feature doesn't work

[GGA-PERSO]

What happened + What you expected to happen

As your doc mentions it should be possible to add custom feature (I copy paste your function from README)
=> but nothing happens after a few longs minutes

Could you please check ?

Versions / Dependencies

0.4.2 (the last one)

Reproduction script

import pandas as pd
import numpy as np
from tsfeatures import tsfeatures

periods = 24
ind = pd.date_range(start='2021-01-01', periods=periods, freq='MS')
vals = np.random.rand(periods)
df = pd.DataFrame({'ds':ind, 'y':vals, 'unique_id':1})

def number_zeros(x, freq):
number = (x == 0).sum()
return {'number_zeros': number}

features_df = tsfeatures(df,freq=12, features=[number_zeros])
features_df

Issue Severity

None

[truonghm]

I'm having a similar issue. If I understand correctly, the number_zeros function will count the number of zeros for each unique_id.

def number_zeros(x, freq):

    number = (x == 0).sum()
    return {'number_zeros': number}

features = tsf.tsfeatures(data, features=[tsf.stl_features, number_zeros], dict_freqs={'MS': 12,})

Result is wrong because number_zeros is not supposed to be all zeros like this. In the data there are some unique ids that contain zeros.

	unique_id	number_zeros
0	282998	0
1	347809	0
2	489552	0
3	594474	0
4	594861	0
5	595209	0
6	595956	0
7	600426	0
8	600429	0

Currently I'm having to do this instead:

features = pd.merge(
    data[["unique_id", "y"]].query("y>0").groupby("unique_id").count().reset_index(),
    features,
    how="left",
    on="unique_id",
)

features.rename(columns={"y": "series_length"}, inplace=True)

[ngupta23]

I think that the issue is that the scale argument in ts_features is set to True by default. You should try to change that to False and then rerun.