Python Pandas 条件无法准确识别行

Question

这是来自 jupyter notebook 的输入和输出。我需要帮助确定我无法准确选择和设置“went_out”列中的数据的原因。

两个红色下划线单元格都应该显示其所在行的日期时间列中的数据，但只有一个单元格准确地显示了它。事实证明，许多符合我条件的行没有被选中和设置。

这是我使用的代码示例：

# your answer here
df.loc[(df['reading_type'] == 'motion') & (df['value'] == 255), 'event'] = 'motion on'
df.loc[(df['reading_type'] == 'motion') & (df['value'] == 0), 'event'] = 'motion off'

df2 = df.loc[(df['reading_type'] == 'door') | (df['event'] == 'motion on')].copy()
df2.loc[(df['event'] == 'door close') & (df['event'].shift(-1) == 'door open'), 'went_out'] = df2['datetime']
df2

这里是 jupyter notebook 文件和 csv 文件的链接：

1. Jupyter 笔记本： https://drive.google.com/file/d/15f6NQrM4UoAZlzRhK35TOKyhPJnmWWdU/view?usp=sharing

2. CSV 文件： https://drive.google.com/file/d/1hZudSVbT91ESj2qkzrJ--CbVdrzVCmce/view?usp=sharing

Answer 1

据我了解，您正在尝试写门关闭的日期和时间。这可能是您想要的解决方案的一部分。您可以只使用关门条件来索引“went_out”列，而不是寻找门打开然后关闭的条件。

df.loc[(df['reading_type'] == 'door') & (df['value'] == 255), 'event'] = 'door on'
df.loc[(df['reading_type'] == 'door') & (df['value'] == 0), 'event'] = 'door off'

df2 = df[df['reading_type'] == 'door'].copy()
# The line below is modified
df2.loc[df2['event'] == 'door off', 'went_out'] = df2[df2['event'] == 'door off']['datetime']
print(df2)

输出如下：

    id  datetime    device  location    reading_type    value   event   went_out
284 284 2018-01-01 07:57:56 Door    door    door    255.0   door on NaN
285 285 2018-01-01 07:58:12 Door    door    door    0.0 door off    2018-01-01 07:58:12
294 294 2018-01-01 08:29:25 Door    door    door    255.0   door on NaN
295 295 2018-01-01 08:29:38 Door    door    door    0.0 door off    2018-01-01 08:29:38
357 357 2018-01-01 09:16:38 Door    door    door    255.0   door on NaN
361 361 2018-01-01 09:17:40 Door    door    door    0.0 door off    2018-01-01 09:17:40

希望这有帮助。

编辑
获取开门后关门的日期和时间的条件

df2.loc[((df2['event'].shift(-1) == 'door on') & (df2['event']=='door off') ), 'went_out'] = df2[df2['event']=='door off']['datetime']

print(df2[df2['event'] == 'door off'])

    id  datetime    device  location    reading_type    value   event   went_out
285 285 2018-01-01 07:58:12 Door    door    door    0.0 door off    2018-01-01 07:58:12
295 295 2018-01-01 08:29:38 Door    door    door    0.0 door off    NaN
361 361 2018-01-01 09:17:40 Door    door    door    0.0 door off    2018-01-01 09:17:40
509 509 2018-01-01 15:50:46 Door    door    door    0.0 door off    2018-01-01 15:50:46

如果这能解决您的问题，请告诉我。