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车辆电耗变化情况

importpandasaspd
df=pd.read_excel('D:\qi\车辆行驶里程表-2.xlsx')df
<>:1: SyntaxWarning: invalid escape sequence '\q' <>:1: SyntaxWarning: invalid escape sequence '\q' C:\Users\琪-\AppData\Local\Temp\ipykernel_42068\927100219.py:1: SyntaxWarning: invalid escape sequence '\q' df=pd.read_excel('D:\qi\车辆行驶里程表-2.xlsx')
车辆ID启动时间停止时间启动时剩余电量停止时剩余电量启动时电池温度峰值速度平均速度
01.02020-02-20 11:31:272020-02-20 11:59:4553451185.21931.80
11.02020-02-20 07:52:512020-02-20 08:19:256253882.79731.62
21.02020-02-13 12:44:462020-02-13 13:13:3087791376.45335.50
31.02020-02-13 07:30:162020-02-13 07:56:5894871167.23429.21
41.02020-02-10 17:21:112020-02-10 17:57:2349411382.98424.86
...........................
5992638350.02020-02-20 08:02:362020-02-20 08:21:341008823102.81363.27
5992750477.02020-02-20 17:52:272020-02-20 18:24:29968120101.98463.68
5992812070.02020-02-20 10:52:482020-02-20 11:04:369990987.35961.02
5992923950.02020-02-20 14:48:172020-02-20 15:53:09946015102.35960.12
5993067818.02020-02-20 10:44:502020-02-20 12:43:02961519102.53175.63

59931 rows × 8 columns

df_car100=df.query("车辆ID==100").reset_index(drop=True)df_car100
车辆ID启动时间停止时间启动时剩余电量停止时剩余电量启动时电池温度峰值速度平均速度
0100.02020-02-20 16:04:112020-02-20 16:41:2758371288.9380030.59
1100.02020-02-19 15:56:412020-02-19 16:31:1173591570.3130020.87
2100.02020-02-19 11:48:332020-02-19 12:32:5186671168.0780023.02
3100.02020-02-19 10:46:442020-02-19 11:28:1092761058.7660026.07
4100.02020-02-17 16:20:482020-02-17 17:14:2433111478.6090027.99
5100.02020-02-16 16:43:552020-02-16 17:04:5154371076.0000037.26
6100.02020-02-16 13:32:332020-02-16 13:58:076444665.7500028.16
7100.02020-02-10 17:49:092020-02-10 18:11:1978621773.4690035.19
8100.02020-01-09 19:13:232020-01-09 19:40:594938770.9690028.26
9100.02020-01-05 19:47:542020-01-05 20:29:546854765.8440028.57
10100.02019-12-20 16:46:342019-12-20 17:14:1020161644.0470028.26
11100.02019-12-20 15:02:592019-12-20 15:40:1732201272.6410032.17
12100.02019-12-06 15:21:082019-12-06 15:47:1046421151.8750029.96
13100.02019-12-06 14:43:132019-12-06 15:01:435346966.5780038.92
14100.02019-11-13 12:37:452019-11-13 13:00:5362561562.0156328.53
15100.02019-11-07 13:37:072019-11-07 14:11:3393871849.0781326.14
16100.02019-09-17 12:51:052019-09-17 14:12:4997532380.9218862.40
time=pd.Timestamp(2020,1,1)print(time)df_car100_before2020=df_car100.query('停止时间<@time').reset_index(drop=True)df_car100_before2020
2020-01-01 00:00:00
车辆ID启动时间停止时间启动时剩余电量停止时剩余电量启动时电池温度峰值速度平均速度
0100.02019-12-20 16:46:342019-12-20 17:14:1020161644.0470028.26
1100.02019-12-20 15:02:592019-12-20 15:40:1732201272.6410032.17
2100.02019-12-06 15:21:082019-12-06 15:47:1046421151.8750029.96
3100.02019-12-06 14:43:132019-12-06 15:01:435346966.5780038.92
4100.02019-11-13 12:37:452019-11-13 13:00:5362561562.0156328.53
5100.02019-11-07 13:37:072019-11-07 14:11:3393871849.0781326.14
6100.02019-09-17 12:51:052019-09-17 14:12:4997532380.9218862.40
df_car100_after2020=df_car100.loc[df_car100['停止时间']>time,:].reset_index(drop=True)df_car100_before2020
车辆ID启动时间停止时间启动时剩余电量停止时剩余电量启动时电池温度峰值速度平均速度
0100.02019-12-20 16:46:342019-12-20 17:14:1020161644.0470028.26
1100.02019-12-20 15:02:592019-12-20 15:40:1732201272.6410032.17
2100.02019-12-06 15:21:082019-12-06 15:47:1046421151.8750029.96
3100.02019-12-06 14:43:132019-12-06 15:01:435346966.5780038.92
4100.02019-11-13 12:37:452019-11-13 13:00:5362561562.0156328.53
5100.02019-11-07 13:37:072019-11-07 14:11:3393871849.0781326.14
6100.02019-09-17 12:51:052019-09-17 14:12:4997532380.9218862.40
importpandasaspd
df=pd.read_excel('D:\qi\车辆行驶里程表-2.xlsx')df
<>:1: SyntaxWarning: invalid escape sequence '\q' <>:1: SyntaxWarning: invalid escape sequence '\q' C:\Users\琪-\AppData\Local\Temp\ipykernel_42068\1507251596.py:1: SyntaxWarning: invalid escape sequence '\q' df = pd.read_excel('D:\qi\车辆行驶里程表-2.xlsx')
车辆ID启动时间停止时间启动时剩余电量停止时剩余电量启动时电池温度峰值速度平均速度
01.02020-02-20 11:31:272020-02-20 11:59:4553451185.21931.80
11.02020-02-20 07:52:512020-02-20 08:19:256253882.79731.62
21.02020-02-13 12:44:462020-02-13 13:13:3087791376.45335.50
31.02020-02-13 07:30:162020-02-13 07:56:5894871167.23429.21
41.02020-02-10 17:21:112020-02-10 17:57:2349411382.98424.86
...........................
5992638350.02020-02-20 08:02:362020-02-20 08:21:341008823102.81363.27
5992750477.02020-02-20 17:52:272020-02-20 18:24:29968120101.98463.68
5992812070.02020-02-20 10:52:482020-02-20 11:04:369990987.35961.02
5992923950.02020-02-20 14:48:172020-02-20 15:53:09946015102.35960.12
5993067818.02020-02-20 10:44:502020-02-20 12:43:02961519102.53175.63

59931 rows × 8 columns

df_car100=df.query("车辆ID==100").reset_index(drop=True)df_car100
车辆ID启动时间停止时间启动时剩余电量停止时剩余电量启动时电池温度峰值速度平均速度
0100.02020-02-20 16:04:112020-02-20 16:41:2758371288.9380030.59
1100.02020-02-19 15:56:412020-02-19 16:31:1173591570.3130020.87
2100.02020-02-19 11:48:332020-02-19 12:32:5186671168.0780023.02
3100.02020-02-19 10:46:442020-02-19 11:28:1092761058.7660026.07
4100.02020-02-17 16:20:482020-02-17 17:14:2433111478.6090027.99
5100.02020-02-16 16:43:552020-02-16 17:04:5154371076.0000037.26
6100.02020-02-16 13:32:332020-02-16 13:58:076444665.7500028.16
7100.02020-02-10 17:49:092020-02-10 18:11:1978621773.4690035.19
8100.02020-01-09 19:13:232020-01-09 19:40:594938770.9690028.26
9100.02020-01-05 19:47:542020-01-05 20:29:546854765.8440028.57
10100.02019-12-20 16:46:342019-12-20 17:14:1020161644.0470028.26
11100.02019-12-20 15:02:592019-12-20 15:40:1732201272.6410032.17
12100.02019-12-06 15:21:082019-12-06 15:47:1046421151.8750029.96
13100.02019-12-06 14:43:132019-12-06 15:01:435346966.5780038.92
14100.02019-11-13 12:37:452019-11-13 13:00:5362561562.0156328.53
15100.02019-11-07 13:37:072019-11-07 14:11:3393871849.0781326.14
16100.02019-09-17 12:51:052019-09-17 14:12:4997532380.9218862.40
time=pd.Timestamp(2020,1,1)print(time)df_car100_before2020=df_car100.query('停止时间<@time').reset_index(drop=True)df_car100_before2020
2020-01-01 00:00:00
车辆ID启动时间停止时间启动时剩余电量停止时剩余电量启动时电池温度峰值速度平均速度
0100.02019-12-20 16:46:342019-12-20 17:14:1020161644.0470028.26
1100.02019-12-20 15:02:592019-12-20 15:40:1732201272.6410032.17
2100.02019-12-06 15:21:082019-12-06 15:47:1046421151.8750029.96
3100.02019-12-06 14:43:132019-12-06 15:01:435346966.5780038.92
4100.02019-11-13 12:37:452019-11-13 13:00:5362561562.0156328.53
5100.02019-11-07 13:37:072019-11-07 14:11:3393871849.0781326.14
6100.02019-09-17 12:51:052019-09-17 14:12:4997532380.9218862.40
df_car100_before2020=df_car100.loc[df_car100['停止时间']>time,:].reset_index(drop=True)df_car100_before2020
车辆ID启动时间停止时间启动时剩余电量停止时剩余电量启动时电池温度峰值速度平均速度
0100.02020-02-20 16:04:112020-02-20 16:41:2758371288.93830.59
1100.02020-02-19 15:56:412020-02-19 16:31:1173591570.31320.87
2100.02020-02-19 11:48:332020-02-19 12:32:5186671168.07823.02
3100.02020-02-19 10:46:442020-02-19 11:28:1092761058.76626.07
4100.02020-02-17 16:20:482020-02-17 17:14:2433111478.60927.99
5100.02020-02-16 16:43:552020-02-16 17:04:5154371076.00037.26
6100.02020-02-16 13:32:332020-02-16 13:58:076444665.75028.16
7100.02020-02-10 17:49:092020-02-10 18:11:1978621773.46935.19
8100.02020-01-09 19:13:232020-01-09 19:40:594938770.96928.26
9100.02020-01-05 19:47:542020-01-05 20:29:546854765.84428.57
df_car100_before2020['电量消耗']=df_car100_before2020['启动时剩余电量']=df_car100_before2020['停止时剩余电量']df_car100_before2020
车辆ID启动时间停止时间启动时剩余电量停止时剩余电量启动时电池温度峰值速度平均速度电量消耗
0100.02020-02-20 16:04:112020-02-20 16:41:2737371288.93830.5937
1100.02020-02-19 15:56:412020-02-19 16:31:1159591570.31320.8759
2100.02020-02-19 11:48:332020-02-19 12:32:5167671168.07823.0267
3100.02020-02-19 10:46:442020-02-19 11:28:1076761058.76626.0776
4100.02020-02-17 16:20:482020-02-17 17:14:2411111478.60927.9911
5100.02020-02-16 16:43:552020-02-16 17:04:5137371076.00037.2637
6100.02020-02-16 13:32:332020-02-16 13:58:074444665.75028.1644
7100.02020-02-10 17:49:092020-02-10 18:11:1962621773.46935.1962
8100.02020-01-09 19:13:232020-01-09 19:40:593838770.96928.2638
9100.02020-01-05 19:47:542020-01-05 20:29:545454765.84428.5754
# 计算行驶时df_car100_before2020['行驶时长delta']=df_car100_before2020['停止时间']-df_car100_before2020['启动时间']df_car100_before2020['行驶时长s']=df_car100_before2020['行驶时长delta'].dt.seconds# 计算行驶里程,并使用round函数保留整数df_car100_before2020['行驶里程']=round((df_car100_before2020['行驶时长s']/3600)*df_car100_before2020['平均速度'])df_car100_before2020
车辆ID启动时间停止时间启动时剩余电量停止时剩余电量启动时电池温度峰值速度平均速度电量消耗行驶时长delta行驶时长s行驶里程
0100.02020-02-20 16:04:112020-02-20 16:41:2737371288.93830.59370 days 00:37:16223619.0
1100.02020-02-19 15:56:412020-02-19 16:31:1159591570.31320.87590 days 00:34:30207012.0
2100.02020-02-19 11:48:332020-02-19 12:32:5167671168.07823.02670 days 00:44:18265817.0
3100.02020-02-19 10:46:442020-02-19 11:28:1076761058.76626.07760 days 00:41:26248618.0
4100.02020-02-17 16:20:482020-02-17 17:14:2411111478.60927.99110 days 00:53:36321625.0
5100.02020-02-16 16:43:552020-02-16 17:04:5137371076.00037.26370 days 00:20:56125613.0
6100.02020-02-16 13:32:332020-02-16 13:58:074444665.75028.16440 days 00:25:34153412.0
7100.02020-02-10 17:49:092020-02-10 18:11:1962621773.46935.19620 days 00:22:10133013.0
8100.02020-01-09 19:13:232020-01-09 19:40:593838770.96928.26380 days 00:27:36165613.0
9100.02020-01-05 19:47:542020-01-05 20:29:545454765.84428.57540 days 00:42:00252020.0
soc_div_odo_before2020=df_car100_before2020['电量消耗'].sum()/df_car100_before2020['行驶里程'].sum()soc_div_odo_before2020
np.float64(2.993827160493827)
defget_soc_div_odo(df):""" df: 需要计算【总电量消耗/总行驶里程】的表格 Return: 总电量消耗/总行驶里程 """df['电量消耗']=df['启动时剩余电量']-df['停止时剩余电量']df['行驶时长delta']=df['停止时间']-df['启动时间']df['行驶时长s']=df['行驶时长delta'].dt.seconds df['行驶里程']=(df['行驶时长s']/60/60*df['平均速度']).round(0)returndf['电量消耗'].sum()/df['行驶里程'].sum()
get_soc_div_odo(df_car100_before2020)
np.float64(0.0)
get_soc_div_odo(df_car100_after2020)
np.float64(1.0493827160493827)
http://www.jsqmd.com/news/617424/

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