#讀取taxiod訂單表 #刪除練習 import pandas as pd taxiod = pd.read_csv(r'data-sample/TaxiOD.csv',header=None) # 要加上后綴名 .csv taxiod.columns=['VehicleNum','Stime','SLng','SLat','ELng','ELat','Etime'] taxiod C:\Program Files (x86)\Anaconda3\lib\site-packages\IPython\core\interactiveshell.py:3146: DtypeWarning: Columns (0,2,3,4,5) have mixed types.Specify dtype option on import or set low_memory=False.has_raised = await self.run_ast_nodes(code_ast.body, cell_name, VehicleNumStimeSLngSLatELngELatEtime01234...464714464715464716464717464718

VehicleNum	Stime	SLng	SLat	ELng	ELat	Etime
22223	00:03:23	114.16746499999999	22.562468	114.22523500000001	22.55275	00:10:48
22223	00:11:33	114.22715	22.554167	114.22921799999999	22.560217	00:15:19
22223	00:17:13	114.23135400000001	22.562166	114.255798	22.590967000000003	00:29:06
22223	00:36:45	114.240196	22.56365	114.119965	22.566668	00:54:42
...	...	...	...	...	...	...
36947	22:39:12	114.006	22.5481	113.996	22.5371	22:46:25
36947	22:49:38	113.995	22.535	113.922	22.4965	23:13:15
36947	23:24:24	113.921	22.5135	113.93	22.4942	23:30:32
36947	23:37:09	113.928	22.5126	113.911	22.4879	23:49:10
36947	23:52:18	113.91	22.4876	NaN	NaN	NaN

464719 rows × 7 columns

taxiod=taxiod.drop([0]) # 刪除第一行 taxiod.index = range(len(taxiod)) # 重新排序索引 taxiod VehicleNumStimeSLngSLatELngELatEtime01234...464713464714464715464716464717

22223	00:03:23	114.16746499999999	22.562468	114.22523500000001	22.55275	00:10:48
22223	00:11:33	114.22715	22.554167	114.22921799999999	22.560217	00:15:19
22223	00:17:13	114.23135400000001	22.562166	114.255798	22.590967000000003	00:29:06
22223	00:36:45	114.240196	22.56365	114.119965	22.566668	00:54:42
22223	01:01:14	114.13541399999998	22.575933	114.166748	22.608267	01:08:17
...	...	...	...	...	...	...
36947	22:39:12	114.006	22.5481	113.996	22.5371	22:46:25
36947	22:49:38	113.995	22.535	113.922	22.4965	23:13:15
36947	23:24:24	113.921	22.5135	113.93	22.4942	23:30:32
36947	23:37:09	113.928	22.5126	113.911	22.4879	23:49:10
36947	23:52:18	113.91	22.4876	NaN	NaN	NaN

464718 rows × 7 columns

taxiod=taxiod[-taxiod['ELng'].isnull()] # 刪掉最后一行為空的 方法 先找到為空的 然后索引 然后去掉 然后賦值給taxiod tmp= pd.to_datetime(taxiod['Stime']) tmp 0 2021-03-03 00:03:23 1 2021-03-03 00:11:33 2 2021-03-03 00:17:13 3 2021-03-03 00:36:45 4 2021-03-03 01:01:14... 464712 2021-03-03 22:08:22 464713 2021-03-03 22:39:12 464714 2021-03-03 22:49:38 464715 2021-03-03 23:24:24 464716 2021-03-03 23:37:09 Name: Stime, Length: 464717, dtype: datetime64[ns] tmp1=pd.to_datetime(taxiod['Etime']) tmp1 0 2021-03-03 00:10:48 1 2021-03-03 00:15:19 2 2021-03-03 00:29:06 3 2021-03-03 00:54:42 4 2021-03-03 01:08:17... 464712 2021-03-03 22:36:53 464713 2021-03-03 22:46:25 464714 2021-03-03 23:13:15 464715 2021-03-03 23:30:32 464716 2021-03-03 23:49:10 Name: Etime, Length: 464717, dtype: datetime64[ns] Duration=tmp1-tmp Duration taxiod['Duration']=Duration taxiod <ipython-input-10-8b258a85ed6d>:3: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value insteadSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copytaxiod['Duration']=Duration VehicleNumStimeSLngSLatELngELatEtimeDuration01234...464712464713464714464715464716

22223	00:03:23	114.16746499999999	22.562468	114.22523500000001	22.55275	00:10:48	0 days 00:07:25
22223	00:11:33	114.22715	22.554167	114.22921799999999	22.560217	00:15:19	0 days 00:03:46
22223	00:17:13	114.23135400000001	22.562166	114.255798	22.590967000000003	00:29:06	0 days 00:11:53
22223	00:36:45	114.240196	22.56365	114.119965	22.566668	00:54:42	0 days 00:17:57
22223	01:01:14	114.13541399999998	22.575933	114.166748	22.608267	01:08:17	0 days 00:07:03
...	...	...	...	...	...	...	...
36947	22:08:22	113.914	22.5314	113.997	22.5456	22:36:53	0 days 00:28:31
36947	22:39:12	114.006	22.5481	113.996	22.5371	22:46:25	0 days 00:07:13
36947	22:49:38	113.995	22.535	113.922	22.4965	23:13:15	0 days 00:23:37
36947	23:24:24	113.921	22.5135	113.93	22.4942	23:30:32	0 days 00:06:08
36947	23:37:09	113.928	22.5126	113.911	22.4879	23:49:10	0 days 00:12:01

464717 rows × 8 columns

taxiod.rename(columns={'duration': 'Duration'}, inplace=True) # 重命名某列 C:\Program Files (x86)\Anaconda3\lib\site-packages\pandas\core\frame.py:4296: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrameSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copyreturn super().rename( taxiod VehicleNumStimeSLngSLatELngELatEtimeDuration01234...464712464713464714464715464716

22223	00:03:23	114.16746499999999	22.562468	114.22523500000001	22.55275	00:10:48	0 days 00:07:25
22223	00:11:33	114.22715	22.554167	114.22921799999999	22.560217	00:15:19	0 days 00:03:46
22223	00:17:13	114.23135400000001	22.562166	114.255798	22.590967000000003	00:29:06	0 days 00:11:53
22223	00:36:45	114.240196	22.56365	114.119965	22.566668	00:54:42	0 days 00:17:57
22223	01:01:14	114.13541399999998	22.575933	114.166748	22.608267	01:08:17	0 days 00:07:03
...	...	...	...	...	...	...	...
36947	22:08:22	113.914	22.5314	113.997	22.5456	22:36:53	0 days 00:28:31
36947	22:39:12	114.006	22.5481	113.996	22.5371	22:46:25	0 days 00:07:13
36947	22:49:38	113.995	22.535	113.922	22.4965	23:13:15	0 days 00:23:37
36947	23:24:24	113.921	22.5135	113.93	22.4942	23:30:32	0 days 00:06:08
36947	23:37:09	113.928	22.5126	113.911	22.4879	23:49:10	0 days 00:12:01

464717 rows × 8 columns

r=taxiod['Duration'].iloc[0] taxiod['order_time']=taxiod['Duration'].apply(lambda r:r.seconds) <ipython-input-13-d23b5d7f6867>:2: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value insteadSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copytaxiod['order_time']=taxiod['Duration'].apply(lambda r:r.seconds) taxiod.drop(columns=['Duration']) VehicleNumStimeSLngSLatELngELatEtimeorder_time01234...464712464713464714464715464716

22223	00:03:23	114.16746499999999	22.562468	114.22523500000001	22.55275	00:10:48	445
22223	00:11:33	114.22715	22.554167	114.22921799999999	22.560217	00:15:19	226
22223	00:17:13	114.23135400000001	22.562166	114.255798	22.590967000000003	00:29:06	713
22223	00:36:45	114.240196	22.56365	114.119965	22.566668	00:54:42	1077
22223	01:01:14	114.13541399999998	22.575933	114.166748	22.608267	01:08:17	423
...	...	...	...	...	...	...	...
36947	22:08:22	113.914	22.5314	113.997	22.5456	22:36:53	1711
36947	22:39:12	114.006	22.5481	113.996	22.5371	22:46:25	433
36947	22:49:38	113.995	22.535	113.922	22.4965	23:13:15	1417
36947	23:24:24	113.921	22.5135	113.93	22.4942	23:30:32	368
36947	23:37:09	113.928	22.5126	113.911	22.4879	23:49:10	721

464717 rows × 8 columns

taxiod['hour']=taxiod['Stime'].apply(lambda r:r.split(':')[0]) taxiod <ipython-input-15-c7c6b55b9ff2>:1: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value insteadSee the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copytaxiod['hour']=taxiod['Stime'].apply(lambda r:r.split(':')[0]) VehicleNumStimeSLngSLatELngELatEtimeDurationorder_timehour01234...464712464713464714464715464716

22223	00:03:23	114.16746499999999	22.562468	114.22523500000001	22.55275	00:10:48	0 days 00:07:25	445	00
22223	00:11:33	114.22715	22.554167	114.22921799999999	22.560217	00:15:19	0 days 00:03:46	226	00
22223	00:17:13	114.23135400000001	22.562166	114.255798	22.590967000000003	00:29:06	0 days 00:11:53	713	00
22223	00:36:45	114.240196	22.56365	114.119965	22.566668	00:54:42	0 days 00:17:57	1077	00
22223	01:01:14	114.13541399999998	22.575933	114.166748	22.608267	01:08:17	0 days 00:07:03	423	01
...	...	...	...	...	...	...	...	...	...
36947	22:08:22	113.914	22.5314	113.997	22.5456	22:36:53	0 days 00:28:31	1711	22
36947	22:39:12	114.006	22.5481	113.996	22.5371	22:46:25	0 days 00:07:13	433	22
36947	22:49:38	113.995	22.535	113.922	22.4965	23:13:15	0 days 00:23:37	1417	22
36947	23:24:24	113.921	22.5135	113.93	22.4942	23:30:32	0 days 00:06:08	368	23
36947	23:37:09	113.928	22.5126	113.911	22.4879	23:49:10	0 days 00:12:01	721	23

464717 rows × 10 columns

import matplotlib.pyplot as plt fig =plt.figure(1,(7,3),dpi=250) ax =plt.subplot(111) plt.sca(ax)plt.boxplot(taxiod['order_time']/60) plt.ylabel('minutes') plt.xlabel('order time') plt.ylim(0,60)plt.show()

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import matplotlib.pyplot as plt fig = plt.figure(1,(10,5),dpi = 250) ax = plt.subplot(111) plt.sca(ax)#整理數據 hour = taxiod['hour'].drop_duplicates().sort_values() datas = [] for i in range(len(hour)):datas.append(taxiod[taxiod['hour']==hour.iloc[i]]['order_time']/60) #繪制 plt.boxplot(datas) #更改x軸ticks的文字 plt.xticks(range(1,len(hour)+1),list(hour)) ###################################################################################plt.ylabel('Order time(minutes)') plt.xlabel('Order start time') plt.ylim(0,60)plt.show()

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import seaborn as sns fig = plt.figure(1,(10,5),dpi = 250) ax = plt.subplot(111) plt.sca(ax)# 只需一行 sns.boxplot(x='hour',y=taxiod['order_time']/60,data=taxiod,ax=ax)plt.ylabel('order_time(minutes)') plt.xlabel('order start time') plt.ylim(0,(60)) plt.show()

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