pandas - 使用 Pandas 计算时间差(以毫秒为单位)

Question

我有一个数据框timings如下:

    start_ms                     end_ms
0   2020-09-01T08:11:19.336Z     2020-09-01T08:11:19.336Z
1   2020-09-01T08:11:20.652Z     2020-09-01T08:11:20.662Z
2   2020-09-01T08:11:20.670Z     2020-09-01T08:11:20.688Z

我正在尝试计算每行的 start_ms 和 end_ms 之间的时间差(以毫秒为单位)，即我希望得到结果

    start_ms                     end_ms                       diff
0   2020-09-01T08:11:19.336Z     2020-09-01T08:11:19.336Z     0
1   2020-09-01T08:11:20.652Z     2020-09-01T08:11:20.662Z     10
2   2020-09-01T08:11:20.670Z     2020-09-01T08:11:20.688Z     18

我可以将时间戳逐列转换为日期时间，但我不确定是否保留值的顺序。

start_ms_time = pd.to_datetime(timings['start_ms'])
end_ms_time = pd.to_datetime(timings['end_ms'])

是否可以在 timings 中将时间戳转换为日期时间，并添加时间差列？我是否需要进行转换才能获得差异？如何计算以毫秒为单位的时间差？

Answer 1

按 Series.sub 减去列然后使用 Series.dt.components :

start_ms_time = pd.to_datetime(timings['start_ms'])
end_ms_time = pd.to_datetime(timings['end_ms'])

timings['diff'] = end_ms_time.sub(start_ms_time).dt.components.milliseconds
print (timings)
                   start_ms                    end_ms  diff
0  2020-09-01T08:11:19.336Z  2020-09-01T08:11:19.336Z     0
1  2020-09-01T08:11:20.652Z  2020-09-01T08:11:20.662Z    10
2  2020-09-01T08:11:20.670Z  2020-09-01T08:11:20.688Z    18

或者Series.dt.total_seconds乘以 1000 并转换为整数:

timings['diff'] = end_ms_time.sub(start_ms_time).dt.total_seconds().mul(1000).astype(int)
print (timings)
                   start_ms                    end_ms  diff
0  2020-09-01T08:11:19.336Z  2020-09-01T08:11:19.336Z     0
1  2020-09-01T08:11:20.652Z  2020-09-01T08:11:20.662Z    10
2  2020-09-01T08:11:20.670Z  2020-09-01T08:11:20.688Z    18