如何从 pandas 数据帧中挑选 season/month 数年?

How to pick a season/month over several years from a pandas dataframe?

我有一个 pandas 数据框,其中包含连续三年的数据... 有没有简单的方法来选择 summer/winter 个时间段?

目前,我这样做:

df_summer = df[((df.index.month > 5) & (df.index.month < 9))]
df_winter = df[((df.index.month < 3) | (df.index.month == 12))]

但是从 xarray 我习惯了这样的符号:

xa_summer = xa[xa.dt.season=='JJA']

一年我能做到:

df_summer = df['YYYYMMDDHH':'YYYYMMDDHH']

在 pandas 中是否有更直观的方法来选择多年的季节?

谢谢...

未在 pandas yet 中实现。

一个想法是通过 12 取模创建助手 season,添加 3,floor 除以 3,最后 map 通过字典:

rng = pd.date_range('2017-04-03', periods=40, freq='MS')
df = pd.DataFrame({'a': range(40)}, index=rng)  
#print (df)

season = ((df.index.month % 12 + 3) // 3).map({1:'DJF', 2: 'MAM', 3:'JJA', 4:'SON'})
print (season)
Index(['MAM', 'JJA', 'JJA', 'JJA', 'SON', 'SON', 'SON', 'DJF', 'DJF', 'DJF',
       'MAM', 'MAM', 'MAM', 'JJA', 'JJA', 'JJA', 'SON', 'SON', 'SON', 'DJF',
       'DJF', 'DJF', 'MAM', 'MAM', 'MAM', 'JJA', 'JJA', 'JJA', 'SON', 'SON',
       'SON', 'DJF', 'DJF', 'DJF', 'MAM', 'MAM', 'MAM', 'JJA', 'JJA', 'JJA'],
      dtype='object')

df_summer = df[season == 'JJA']
print (df_summer)
             a
2017-06-01   1
2017-07-01   2
2017-08-01   3
2018-06-01  13
2018-07-01  14
2018-08-01  15
2019-06-01  25
2019-07-01  26
2019-08-01  27
2020-06-01  37
2020-07-01  38
2020-08-01  39

df_winter = df[season == 'DJF']
print (df_winter)
             a
2017-12-01   7
2018-01-01   8
2018-02-01   9
2018-12-01  19
2019-01-01  20
2019-02-01  21
2019-12-01  31
2020-01-01  32
2020-02-01  33

或创建新列:

df_summer = df[df['season'] == 'JJA']
print (df_summer)
             a season
2017-06-01   1    JJA
2017-07-01   2    JJA
2017-08-01   3    JJA
2018-06-01  13    JJA
2018-07-01  14    JJA
2018-08-01  15    JJA
2019-06-01  25    JJA
2019-07-01  26    JJA
2019-08-01  27    JJA
2020-06-01  37    JJA
2020-07-01  38    JJA
2020-08-01  39    JJA

df_winter = df[df['season'] == 'DJF']
print (df_winter)
             a season
2017-12-01   7    DJF
2018-01-01   8    DJF
2018-02-01   9    DJF
2018-12-01  19    DJF
2019-01-01  20    DJF
2019-02-01  21    DJF
2019-12-01  31    DJF
2020-01-01  32    DJF
2020-02-01  33    DJF

另一个想法是按月使用 Index.isin

df_summer = df[df.index.month.isin([6,7,8])]
print (df_summer)
             a
2017-06-01   1
2017-07-01   2
2017-08-01   3
2018-06-01  13
2018-07-01  14
2018-08-01  15
2019-06-01  25
2019-07-01  26
2019-08-01  27
2020-06-01  37
2020-07-01  38
2020-08-01  39

df_winter = df[df.index.month.isin([12,1,2])]
print (df_winter)
             a
2017-12-01   7
2018-01-01   8
2018-02-01   9
2018-12-01  19
2019-01-01  20
2019-02-01  21
2019-12-01  31
2020-01-01  32
2020-02-01  33