python - 将带有 DatetimeIndex 的 Pandas DataFrame 按 na 或缺失的行拆分为 block

Question

我有一个带有 DatetimeIndex 的 Pandas DataFrame，我想将它拆分成连续连接的行 block ，删除 nan 行。

                           Temperature  Humidity
2020-01-01 00:00:00+00:00  20           40 
2020-01-01 00:01:00+00:00  21           40
2020-01-01 00:02:00+00:00  NaN          NaN
2020-01-01 00:03:00+00:00  22           41
2020-01-01 00:04:00+00:00  NaN          NaN
2020-01-01 00:05:00+00:00  NaN          NaN
2020-01-01 00:06:00+00:00  NaN          NaN
2020-01-01 00:07:00+00:00  21           41
2020-01-01 00:08:00+00:00  21           41
2020-01-01 00:09:00+00:00  21           42

结果应该是以下三个 DataFrame 的列表:

                           Temperature  Humidity
2020-01-01 00:00:00+00:00  20           40 
2020-01-01 00:01:00+00:00  21           40

                           Temperature  Humidity
2020-01-01 00:03:00+00:00  22           41

                           Temperature  Humidity
2020-01-01 00:07:00+00:00  21           41
2020-01-01 00:08:00+00:00  21           41
2020-01-01 00:09:00+00:00  21           42

有什么帮助吗？

Answer 1

让我们尝试使用 cumsum 和 isnull 创建 groupby 键

d = {x : y for x , y in df.dropna().groupby(df.isnull().cumsum().sum(1))}
d[0]
                          Temperature  Humidity
2020-01-0100:00:00+00:00         20.0      40.0
2020-01-0100:01:00+00:00         21.0      40.0