Python pandas滚动意味着没有修复窗口数

Question

I am looking to add two column [ std_dev , mean ], where the sample of the mean expands as the date continues for the specific location.

location   date              temp    std_dev    mean
NY         2014-02-01        60      
NY         2014-02-02        55      
NY         2014-02-03        70      
NY         2014-02-04        80      
LA         2014-02-01        80      
LA         2014-02-02        85      
LA         2014-02-03        75       

I found a post that explains rolling mean/std and I was able to apply it to the table. However I receive an error for std_dev since the size of the location is not a fixed value. How do I reference the window size without it being fixed?

pandas rolling on a shifted dataframe

df['mean'] = df.groupby('location')['temp'].apply(pd.rolling_mean,4,min_periods=2).shift(1)

df['std_dev'] = df.groupby('location')['temp'].apply(pd.rolling_std,4,min_periods=2).shift(1)

Any help greatly appreciated!

Answer 1

I think you are looking for expanding , eg

>>> df
   temp location
0    60       NY
1    55       NY
2    70       NY
3    80       NY
4    80       LA
5    85       LA
6    75       LA

>>> expander = df.groupby('location').temp.expanding(min_periods=2)

>>> orderify = lambda x: x.reset_index(level=0, drop=True).sort_index()

>>> df['mean'], df['std'] = map(orderify, [expander.mean(), expander.std()])

>>> df
  location  temp       mean        std
0       NY    60        NaN        NaN
1       NY    55  57.500000   3.535534
2       NY    70  61.666667   7.637626
3       NY    80  66.250000  11.086779
4       LA    80        NaN        NaN
5       LA    85  82.500000   3.535534
6       LA    75  80.000000   5.000000

---

Note : It would be nice to use .agg here on expander , but as of version 0.19.2 there isn't sophisticated agg available on groupby.rolling or groupby.expanding , so it is not possible. See

• BUG/ENH: groupby.rolling.agg / Column(s) low already selected #15072