使用值 python 的平均值填充缺失的时间

Question

我有这个数据框缺少了一些时间（我希望它是每一分钟）。请看下面的示例：

time = np.array([pd.to_datetime("2022-01-01 00:00:00"),pd.to_datetime("2022-01-01 00:00:01"),pd.to_datetime("2022-01-01 00:00:03"), pd.to_datetime("2022-01-01 00:00:04"),pd.to_datetime("2022-01-01 00:00:07"),pd.to_datetime("2022-01-01 00:00:09"), pd.to_datetime("2022-01-01 00:00:10")])
lat = [58.1, 58.4, 58.5, 58.9, 59,59.2, 59.5]
lng = [1.34, 1.44, 1.46, 1.48, 1.55, 1.57, 1.59]

df =  pd.DataFrame({"time": time, "lat": lat, "lng" :lng})


time                lat     lng
2022-01-01 00:00:00 58.1    1.34
2022-01-01 00:00:01 58.4    1.44
2022-01-01 00:00:03 58.5    1.46
2022-01-01 00:00:04 58.9    1.48
2022-01-01 00:00:07 59.0    1.55
2022-01-01 00:00:09 59.2    1.57
2022-01-01 00:00:10 59.5    1.59

我想及时填补空白，以便每分钟都有数据，并且 lat/lng 填充中间值的平均值。我的计划是为每一分钟创建一个时间数组，并尝试使用 ffil 或类似的东西来填补缺失的点。但我无法弄清楚如何。预期的输出是这样的

time                lat     lng
2022-01-01 00:00:00 58.1    1.34
2022-01-01 00:00:01 58.4    1.44
2022-01-01 00:00:01 58.45   1.45
2022-01-01 00:00:03 58.5    1.46
2022-01-01 00:00:04 58.9    1.48
2022-01-01 00:00:05 58.933  1.5033
2022-01-01 00:00:06 58.966  1.5233
2022-01-01 00:00:07 59.0    1.55
2022-01-01 00:00:08 59.1    1.56
2022-01-01 00:00:09 59.2    1.57
2022-01-01 00:00:10 59.5    1.59

请给我一些关于如何做到这一点的建议

Answer 1

创建 DatetimeIndex 然后通过 div 添加缺失的时间。DataFrame.asfreq and interpolate by DataFrame.interpolate:

df = df.set_index('time').asfreq(freq='S').interpolate()
print (df)
                           lat       lng
time                                    
2022-01-01 00:00:00  58.100000  1.340000
2022-01-01 00:00:01  58.400000  1.440000
2022-01-01 00:00:02  58.450000  1.450000
2022-01-01 00:00:03  58.500000  1.460000
2022-01-01 00:00:04  58.900000  1.480000
2022-01-01 00:00:05  58.933333  1.503333
2022-01-01 00:00:06  58.966667  1.526667
2022-01-01 00:00:07  59.000000  1.550000
2022-01-01 00:00:08  59.100000  1.560000
2022-01-01 00:00:09  59.200000  1.570000
2022-01-01 00:00:10  59.500000  1.590000

使用值 python 的平均值填充缺失的时间

filling in the missing times using average for the values pythn

python

datetime

dataframe

pandas

imputation