如何解决根据条件填充df的NaN-值并添加行
我有这个df：
df = pd.DataFrame({"Time": ["2020-04-09 06:40:40.559719","2020-04-09 06:40:40.559719",'NaT','2020-04-09 16:50:38.559871','2020-04-29 16:50:38.559871'],"Power": [7500,6000,'NaN',3600,4200],"Total Energy": [5000,5100,5300,5360,5500],"ID": [1,1,2,2],"Energy": [500,600,800,60,200]},index=pd.date_range(start = "2020-04-09 6:45",periods = 10,freq = 'T'))
df['Time'] = pd.to_datetime(df['Time'])
df['Power'] = pd.to_numeric(df['Power'],errors = 'coerce')
df['Total Energy'] = pd.to_numeric(df['Total Energy'],errors = 'coerce')
df['ID'] = pd.to_numeric(df['ID'],errors = 'coerce')
df['Energy'] = pd.to_numeric(df['Energy'],errors = 'coerce')
df
输出：
Time Power Total Energy ID Energy
2020-04-09 06:45:00 2020-04-09 06:40:40.559719 7500.0 5000.0 1.0 500.0
2020-04-09 06:46:00 2020-04-09 06:40:40.559719 6000.0 5100.0 1.0 600.0
2020-04-09 06:47:00 NaT NaN NaN NaN NaN
2020-04-09 06:48:00 2020-04-09 06:40:40.559719 6000.0 5300.0 1.0 800.0
2020-04-09 06:49:00 NaT NaN NaN NaN NaN
2020-04-09 06:50:00 NaT NaN NaN NaN NaN
2020-04-09 06:51:00 NaT NaN NaN NaN NaN
2020-04-09 06:52:00 2020-04-09 16:50:38.559871 3600.0 5360.0 2.0 60.0
2020-04-09 06:53:00 NaT NaN NaN NaN NaN
2020-04-09 06:54:00 2020-04-29 16:50:38.559871 4200.0 5500.0 2.0 200.0
现在我想根据不同的条件填写NaN / NaT值，并在缺少df时添加一些行：
- df ['Time']：创建新行，直到df ['Timestamp'] = df ['Time']
- 填充新行：第一行df ['Energy'] = 0，而不是线性填充；第一行的df ['Power'] = 0，而不是df ['Power'] = df ['Energy'] /（1/60）; df ['Time']和df ['ID']用bfill（）填充； df ['Total Energy'] = df ['Energy']的总和
- 两个不同时间之间的界线：按预期结果填充
- 时间序列中的NaN值（例如@ 2020-04-09 06:47:00）：带有ffill（）的df ['Time']和df ['ID']； df ['Energy'] =现有线之间的差异（如果有更多的NaN线->线性插入）； df ['Total Energy'] =旧值+ df ['Energy']; df ['Power'] = df ['Energy'] /（1/60）
预期输出：
Time Power Total Energy ID Energy
2020-04-09 06:41:00 2020-04-09 06:40:40.559719 0 4500.0 1.0 0
2020-04-09 06:42:00 2020-04-09 06:40:40.559719 7500.0 4625.0 1.0 125.0
2020-04-09 06:43:00 2020-04-09 06:40:40.559719 7500.0 4750.0 1.0 250.0
2020-04-09 06:44:00 2020-04-09 06:40:40.559719 7500.0 4875.0 1.0 375.0
2020-04-09 06:45:00 2020-04-09 06:40:40.559719 7500.0 5000.0 1.0 500.0
2020-04-09 06:46:00 2020-04-09 06:40:40.559719 6000.0 5100.0 1.0 600.0
2020-04-09 06:47:00 2020-04-09 06:40:40.559719 6000.0 5200.0 1.0 700.0
2020-04-09 06:48:00 2020-04-09 06:40:40.559719 6000.0 5300.0 1.0 800.0
2020-04-09 06:49:00 - 0 5300.0 - 0
2020-04-09 06:50:00 - 0 5300.0 - 0
2020-04-09 06:51:00 2020-04-09 16:50:38.559871 0 5300.0 2.0 0
2020-04-09 06:52:00 2020-04-09 16:50:38.559871 3600.0 5360.0 2.0 60.0
2020-04-09 06:53:00 2020-04-09 16:50:38.559871 4200.0 5430.0 2.0 130.0
2020-04-09 06:54:00 2020-04-29 16:50:38.559871 4200.0 5500.0 2.0 200.0
感谢您的帮助！ ：）
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