我有以下数据框:
gcloud container clusters get-credentials
我设法创建了一个'interval'列来指示天气或索引的小时不在16h到18h之间。
我的问题如下:
如何有效地做到这一点?
预期结果:
date = ['2015-02-03 23:00:00','2015-02-03 23:30:00','2015-02-04 00:00:00','2015-02-04 00:30:00','2015-02-04 01:00:00','2015-02-04 01:30:00','2015-02-04 02:00:00','2015-02-04 02:30:00','2015-02-04 03:00:00','2015-02-04 03:30:00','2015-02-04 04:00:00','2015-02-04 04:30:00','2015-02-04 05:00:00','2015-02-04 05:30:00','2015-02-04 06:00:00','2015-02-04 06:30:00','2015-02-04 07:00:00','2015-02-04 07:30:00','2015-02-04 08:00:00','2015-02-04 08:30:00','2015-02-04 09:00:00','2015-02-04 09:30:00','2015-02-04 10:00:00','2015-02-04 10:30:00','2015-02-04 11:00:00','2015-02-04 11:30:00','2015-02-04 12:00:00','2015-02-04 12:30:00','2015-02-04 13:00:00','2015-02-04 13:30:00','2015-02-04 14:00:00','2015-02-04 14:30:00','2015-02-04 15:00:00','2015-02-04 15:30:00','2015-02-04 16:00:00','2015-02-04 16:30:00','2015-02-04 17:00:00','2015-02-04 17:30:00','2015-02-04 18:00:00','2015-02-04 18:30:00','2015-02-04 19:00:00','2015-02-04 19:30:00','2015-02-04 20:00:00','2015-02-04 20:30:00','2015-02-04 21:00:00','2015-02-04 21:30:00','2015-02-04 22:00:00','2015-02-04 22:30:00','2015-02-04 23:00:00','2015-02-04 23:30:00']
value = [33.24 , 31.71 , 34.39 , 34.49 , 34.67 , 34.46 , 34.59 , 34.83 , 35.78 , 33.03 , 35.49 , 33.79 , 36.12 , 37.09 , 39.54 , 41.19 , 45.99 , 50.23 , 46.72 , 47.47 , 48.46 , 48.38 , 48.40 , 48.13 , 38.35 , 38.19 , 38.12 , 38.05 , 38.06 , 37.83 , 37.49 , 37.41 , 41.84 , 42.26 , 44.09 , 48.85 , 50.07 , 50.94 , 51.09 , 50.60 , 47.39 , 45.57 , 45.03 , 44.98 , 41.32 , 40.37 , 41.12 , 39.33 , 35.38 , 33.44 ]
df = pd.DataFrame({'value':value,'index':date})
df.index = pd.to_datetime(df['index'],format='%Y-%m-%d %H:%M')
df.drop(['index'],axis=1,inplace=True)
df['interval'] = ((df.index.hour >= 16) & (df.index.hour <18 ))*1
print(df.head(50))
非常感谢,
答案 0 :(得分:5)
您还可以使用熊猫功能indexer_between_time
。
df.at[df.index[df.index.indexer_between_time("16:30", "18:30")], "interval"] = 1
答案 1 :(得分:3)
也许有一种更清洁的方法(例如,@ vealkind的解决方案,例如 edit:),但这可以满足您的要求:
df['interval'] = (pd.Series(df.index.time)
.between(pd.to_datetime('16:30:00').time(),
pd.to_datetime('18:30:00').time())
.astype(int)
.tolist())
>>> df.iloc[30:42]
value interval
index
2015-02-04 14:00:00 37.49 0
2015-02-04 14:30:00 37.41 0
2015-02-04 15:00:00 41.84 0
2015-02-04 15:30:00 42.26 0
2015-02-04 16:00:00 44.09 0
2015-02-04 16:30:00 48.85 1
2015-02-04 17:00:00 50.07 1
2015-02-04 17:30:00 50.94 1
2015-02-04 18:00:00 51.09 1
2015-02-04 18:30:00 50.60 1
2015-02-04 19:00:00 47.39 0
2015-02-04 19:30:00 45.57 0