在timeseries数据中提取值并计算timeseries持续时间

Question

问题陈述:每辆车column_name= ' SOC‘有多个充放电实例，从本专栏中得到两个新的df (ref必需输出)，得到最小SoC、每辆车充电周期的最大SOC，以及每辆车在特定一天的每一个排放周期和时间(放电)的最小SoC和最大SoC。

df1
Date             Time    vehicle_no  soc     SOC Diff
0   2022-10-01  02:27:56    DL21GD0100  80.0    0
1   2022-10-01  02:28:26    DL21GD0100  80.0    Discharging
2   2022-10-01  02:28:56    DL21GD0100  80.0    Discharging
3   2022-10-01  02:29:26    DL21GD0100  80.0    Discharging
4   2022-10-01  02:29:56    DL21GD0100  69.0    Discharging
5    2022-10-01 02:29:56    DL21GD0100  70.0    Charging
6    2022-10-01 02:30:56    DL21GD0100  71.0    Charging
7    2022-10-01 02:32:56    DL21GD0100  72.0    Charging
8   2022-10-01 03:16:00    DL21GD0100   63.0    Discharging
9  2022-10-01  04:16:30    DL21GD0100    23.0    Discharging
10 2022-10-01  04:16:30    DL21GD0100    24.0    Charging
11 2022-10-01  04:17:00    DL21GD0100    54.0    Charging
12  2022-10-01  09:17:30    WB25M9298   24.0    Charging
13 2022-10-01  10:21:00    WB25M9298   57.0    Charging

Required output

Charging
  Date         Vehicle_no Min_Soc Max_SOC Time_Dur    Total 
                                          (hh:mm:ss)   Consumed_Soc
2022-10-01   DL21GD0100    70.0     72.0     00:03:00     23.0
2022-10-01  DL21GD0100      23.0    54.0     01:01:00     21.0
2022-10-01  WB25M9298     24.0       57.0  01:03:30      33.0

Discharging
SL.No  Date   Vehicle_no  Max_Soc Max_SOC   Time_dur    Total
                                           (hh:mm:ss)  Soc_Disch
1   2022-10-01  DL21GD0100  80.0  69.0    00:02:00      11.0
2   2022-10-01  DL21GD0100  63.0  23.0     01:00:00     40.0

Answer 1

问题陈述：

每个车辆列名称=‘SOC’有多个充放电实例，从该列得到两个新的df(Ref-必需输出)，其中最小SOC、特定车辆的最大SOC，其中status=充电.Similarly获取最小SOC和最大SOC，以及特定一天内每辆车辆的持续时间(放电)。

df1
Date             Time    vehicle_no  soc     SOC Diff
0   2022-10-01  02:27:56    DL21GD0100  80.0    0
1   2022-10-01  02:28:26    DL21GD0100  80.0    Discharging
2   2022-10-01  02:28:56    DL21GD0100  80.0    Discharging
3   2022-10-01  02:29:26    DL21GD0100  80.0    Discharging
4   2022-10-01  02:29:56    DL21GD0100  69.0    Discharging
5    2022-10-01 02:29:56    DL21GD0100  70.0    Charging
6    2022-10-01 02:30:56    DL21GD0100  71.0    Charging
7    2022-10-01 02:32:56    DL21GD0100  72.0    Charging
8   2022-10-01 03:16:00    DL21GD0100   63.0    Discharging
9  2022-10-01  04:16:30    DL21GD0100    23.0    Discharging
10  2022-10-01  04:17:00    DL21GD0100    54.0    Charging
11  2022-10-01  09:17:30    WB25M9298   24.0    Charging
12  2022-10-01  10:21:00    WB25M9298   57.0    Charging

Tried this 
#From the Soc Data identify the Min and Max Soc 

#Set your range
range_min=0
range_max=100

#define the functions to be applied
#evaluate if soc is low

def eval_low(soc):
    if soc <= range_min:
        return soc
    else:
        return 0
#evaluate if soc is high   
def eval_high(soc):
    if soc >= range_max:
        return soc
    else:
        return 0
    
    
#evaluate the functions in a new column
df2['Min_soc']=df2.soc.apply(eval_low)
df2['Max_soc']=df2.soc.apply(eval_high)
    
Doesn't serve the purpose

Required output


Charging
  Date         Vehicle_no Min_Soc Max_SOC Time_Dur    Total 
                                          (hh:mm:ss)   Consumed_Soc
2022-10-01   DL21GD0100    70.0     72.0     00:03:00     23.0
2022-10-01  DL21GD0100      23.0    54.0     01:01:00     21.0
2022-10-01  WB25M9298     24.0       57.0  01:03:30      33.0
Where Time Duration for charging= time at Max_Soc- time at Min_SOC

Discharging
SL.No  Date   Vehicle_no  Max_Soc Max_SOC   Time_dur    Total
                                           (hh:mm:ss)  Soc_Disch
1   2022-10-01  DL21GD0100  80.0  69.0    00:02:00      11.0
2   2022-10-01  DL21GD0100  63.0  23.0     01:00:00     40.0
Where Time Duration for discharging= time at Max_Soc- time at Min_SOC