我有这个{a1}与数据收集超过34天,15分钟的间隔
如何从一天中的同一时间获取所有数据?我已经加载数据集并将其转换为DateTime格式
我已经获得了以下代码:
tmp=weather_sensor_df()
df=pd.DataFrame(columns=tmp.columns)
print(df)
tmp.DATE_TIME.dt.hour[13]
for i in tmp.index:
time = tmp.DATE_TIME[i]
if time.hour==13 and time.minute==0:
dict={
df.columns[0]:time,
df.columns[1]:tmp.AMBIENT_TEMPERATURE[i],
df.columns[2]:tmp.MODULE_TEMPERATURE[i],
df.columns[3]:tmp.IRRADIATION[i],
}
df=df.append(dict,ignore_index=True)
参考:weather_sensor_df()
加载天气传感器数据帧,并使用pd.DataFrame.to_datetime()
将DATE_TIME
设置为Timestamp
格式
我认为groupby()
函数更适合这种情况,但我不确定如何继续
DATE_TIME,PLANT_ID,SOURCE_KEY,AMBIENT_TEMPERATURE,MODULE_TEMPERATURE,IRRADIATION
2020-05-15 00:00:00,4135001,HmiyD2TTLFNqkNe,25.184316133333333,22.8575074,0.0
2020-05-15 00:15:00,4135001,HmiyD2TTLFNqkNe,25.08458866666667,22.761667866666663,0.0
2020-05-15 00:30:00,4135001,HmiyD2TTLFNqkNe,24.935752600000004,22.59230553333333,0.0
2020-05-15 00:45:00,4135001,HmiyD2TTLFNqkNe,24.8461304,22.36085213333333,0.0
2020-05-15 01:00:00,4135001,HmiyD2TTLFNqkNe,24.621525357142858,22.165422642857145,0.0
2020-05-15 01:15:00,4135001,HmiyD2TTLFNqkNe,24.5360922,21.968570866666667,0.0
2020-05-15 01:30:00,4135001,HmiyD2TTLFNqkNe,24.638673866666664,22.352925666666668,0.0
2020-05-15 01:45:00,4135001,HmiyD2TTLFNqkNe,24.87302233333333,23.1609192,0.0
2020-05-15 02:00:00,4135001,HmiyD2TTLFNqkNe,24.936930466666663,23.026113,0.0
2020-05-15 02:15:00,4135001,HmiyD2TTLFNqkNe,25.0122476,23.343229266666665,0.0
2020-06-17 21:30:00,4135001,HmiyD2TTLFNqkNe,22.9965616,21.869773466666665,0.0
2020-06-17 21:45:00,4135001,HmiyD2TTLFNqkNe,23.137091,22.1259848,0.0
2020-06-17 22:00:00,4135001,HmiyD2TTLFNqkNe,22.563179466666668,21.164713466666665,0.0
2020-06-17 22:15:00,4135001,HmiyD2TTLFNqkNe,22.19922893333333,20.51527293333333,0.0
2020-06-17 22:30:00,4135001,HmiyD2TTLFNqkNe,22.171736666666664,21.0808288,0.0
2020-06-17 22:45:00,4135001,HmiyD2TTLFNqkNe,22.150569666666662,21.480377266666668,0.0
2020-06-17 23:00:00,4135001,HmiyD2TTLFNqkNe,22.129815666666666,21.38902386666667,0.0
2020-06-17 23:15:00,4135001,HmiyD2TTLFNqkNe,22.008274642857145,20.709211357142856,0.0
2020-06-17 23:30:00,4135001,HmiyD2TTLFNqkNe,21.96949473333333,20.7349628,0.0
2020-06-17 23:45:00,4135001,HmiyD2TTLFNqkNe,21.909287666666668,20.4279724,0.0
pandas.DataFrame.groupby
表示.dt.time
。dfg
是一个DataFrameGroupBy
对象李>GroupBy
对象,可以在isoformat
(例如'hh:mm:ss'
)中创建数据帧的dict
作为键。.dt.hour
用于组,则删除.isoformat
,并且keys
将是ints
(0...23
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