根据条件获取日期间隔之间的重叠时长

Question

我有两个数据框，它们有一个 start/end 日期时间和一个值。行数不一样。重叠的区间不一定在同一个row/index.

df1

start_datetime   end_datetime   value
08:50            09:50          5
09:52            10:10          6
10:50            11:30          2

df2

start_datetime   end_datetime   value
08:51            08:59          3
09:52            10:02          9
10:03            10:30          1
11:03            11:39          1
13:10            13:15          0

我想计算 df1 和 df2 仅在 df1.value > df2.value 重叠时的持续时间总和。在一个df2时间间隔内，df1可以重叠多次，有时条件为真。

我试过类似的东西：

            time = timedelta()
            for i, row1 in df1.iterrows():
                t1 = pd.Interval(row1.start, row1.end)
                for j, row2 in df2.iterrows():
                    t2 = pd.Interval(row2.start, row2.end)
                    if t1.overlaps(t2) and row1.value > row2.value:
                        latest_start = np.maximum(row1.start, row1.start)
                        earliest_end = np.minimum(row2.end, row2.end)
                        delta = earliest_end - latest_start
                        time += delta

我可以在每个 df1 行上循环并使用整个 df2 数据进行测试，但它没有优化。

预期输出（示例）：

Timedelta('0 days 00:99:99')

Answer 1

这是我的解决方案：

创建数据帧：

df1 = pd.DataFrame(
    {"start_datetime1": ['08:50' ,'09:52' ,'10:50 ' ],  
     'end_datetime1' : ['09:50','10:10','11:30'] , 
     'value1': [5,6,2]})

df2 = pd.DataFrame(
      {"start_datetime2": ['08:51' ,'09:52' ,'10:03 ','11:03 ','13:10 ' ], 
       'end_datetime2' : ['08:59','10:02','10:30','11:39', '13:15'] ,
       'value2': [3,9,1,1,0]})

df2["start_datetime2"]= pd.to_datetime(df2["start_datetime2"])
df2["end_datetime2"]= pd.to_datetime(df2["end_datetime2"])

df1["start_datetime1"]= pd.to_datetime(df1["start_datetime1"])
df1["end_datetime1"]= pd.to_datetime(df1["end_datetime1"])

合并数据帧，使比较更容易。组合数据框具有所有可能的匹配项：

df1['temp'] = 1 #temporary keys to create all combinations
df2['temp'] = 1
df_combined = pd.merge(df1,df2,on='temp').drop('temp',axis=1)

用 lambda 函数比较值：

df_combined['Result'] = df_combined.apply(lambda row: max(row["start_datetime1"],row["start_datetime2"]) -
                                         min(row["start_datetime1"],row["start_datetime2"]) 
                                         if pd.Interval(row['start_datetime1'], row['end_datetime1']).overlaps(
                                             pd.Interval(row['start_datetime2'], row['end_datetime2'])) and
                                             row["value1"] > row["value2"] 
                                             else 0, axis = 1 )
df_combined

结果：

total_timedelta = df_combined['Result'].loc[df_combined['Result'] != 0].sum()
0 days 00:25:00

数据框：

根据条件获取日期间隔之间的重叠时长

Get the overlap duration between date intervals based on condition

python

pandas

overlap