#读取taxiod订单表

#删除练习

import pandas as pd
taxiod = pd.read_csv(r'data-sample/TaxiOD.csv',header=None) # 要加上后缀名 .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,
VehicleNum Stime SLng SLat ELng ELat Etime
0 VehicleNum Stime SLng SLat ELng ELat Etime
1 22223 00:03:23 114.16746499999999 22.562468 114.22523500000001 22.55275 00:10:48
2 22223 00:11:33 114.22715 22.554167 114.22921799999999 22.560217 00:15:19
3 22223 00:17:13 114.23135400000001 22.562166 114.255798 22.590967000000003 00:29:06
4 22223 00:36:45 114.240196 22.56365 114.119965 22.566668 00:54:42
... ... ... ... ... ... ... ...
464714 36947 22:39:12 114.006 22.5481 113.996 22.5371 22:46:25
464715 36947 22:49:38 113.995 22.535 113.922 22.4965 23:13:15
464716 36947 23:24:24 113.921 22.5135 113.93 22.4942 23:30:32
464717 36947 23:37:09 113.928 22.5126 113.911 22.4879 23:49:10
464718 36947 23:52:18 113.91 22.4876 NaN NaN NaN

464719 rows × 7 columns

taxiod=taxiod.drop([0])  # 删除第一行

taxiod.index = range(len(taxiod)) # 重新排序索引

taxiod
VehicleNum Stime SLng SLat ELng ELat Etime
0 22223 00:03:23 114.16746499999999 22.562468 114.22523500000001 22.55275 00:10:48
1 22223 00:11:33 114.22715 22.554167 114.22921799999999 22.560217 00:15:19
2 22223 00:17:13 114.23135400000001 22.562166 114.255798 22.590967000000003 00:29:06
3 22223 00:36:45 114.240196 22.56365 114.119965 22.566668 00:54:42
4 22223 01:01:14 114.13541399999998 22.575933 114.166748 22.608267 01:08:17
... ... ... ... ... ... ... ...
464713 36947 22:39:12 114.006 22.5481 113.996 22.5371 22:46:25
464714 36947 22:49:38 113.995 22.535 113.922 22.4965 23:13:15
464715 36947 23:24:24 113.921 22.5135 113.93 22.4942 23:30:32
464716 36947 23:37:09 113.928 22.5126 113.911 22.4879 23:49:10
464717 36947 23:52:18 113.91 22.4876 NaN NaN NaN

464718 rows × 7 columns

taxiod=taxiod[-taxiod['ELng'].isnull()] # 删掉最后一行为空的   方法  先找到为空的 然后索引 然后去掉  然后赋值给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
VehicleNum Stime SLng SLat ELng ELat Etime Duration
0 22223 00:03:23 114.16746499999999 22.562468 114.22523500000001 22.55275 00:10:48 0 days 00:07:25
1 22223 00:11:33 114.22715 22.554167 114.22921799999999 22.560217 00:15:19 0 days 00:03:46
2 22223 00:17:13 114.23135400000001 22.562166 114.255798 22.590967000000003 00:29:06 0 days 00:11:53
3 22223 00:36:45 114.240196 22.56365 114.119965 22.566668 00:54:42 0 days 00:17:57
4 22223 01:01:14 114.13541399999998 22.575933 114.166748 22.608267 01:08:17 0 days 00:07:03
... ... ... ... ... ... ... ... ...
464712 36947 22:08:22 113.914 22.5314 113.997 22.5456 22:36:53 0 days 00:28:31
464713 36947 22:39:12 114.006 22.5481 113.996 22.5371 22:46:25 0 days 00:07:13
464714 36947 22:49:38 113.995 22.535 113.922 22.4965 23:13:15 0 days 00:23:37
464715 36947 23:24:24 113.921 22.5135 113.93 22.4942 23:30:32 0 days 00:06:08
464716 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
VehicleNum Stime SLng SLat ELng ELat Etime Duration
0 22223 00:03:23 114.16746499999999 22.562468 114.22523500000001 22.55275 00:10:48 0 days 00:07:25
1 22223 00:11:33 114.22715 22.554167 114.22921799999999 22.560217 00:15:19 0 days 00:03:46
2 22223 00:17:13 114.23135400000001 22.562166 114.255798 22.590967000000003 00:29:06 0 days 00:11:53
3 22223 00:36:45 114.240196 22.56365 114.119965 22.566668 00:54:42 0 days 00:17:57
4 22223 01:01:14 114.13541399999998 22.575933 114.166748 22.608267 01:08:17 0 days 00:07:03
... ... ... ... ... ... ... ... ...
464712 36947 22:08:22 113.914 22.5314 113.997 22.5456 22:36:53 0 days 00:28:31
464713 36947 22:39:12 114.006 22.5481 113.996 22.5371 22:46:25 0 days 00:07:13
464714 36947 22:49:38 113.995 22.535 113.922 22.4965 23:13:15 0 days 00:23:37
464715 36947 23:24:24 113.921 22.5135 113.93 22.4942 23:30:32 0 days 00:06:08
464716 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'])
VehicleNum Stime SLng SLat ELng ELat Etime order_time
0 22223 00:03:23 114.16746499999999 22.562468 114.22523500000001 22.55275 00:10:48 445
1 22223 00:11:33 114.22715 22.554167 114.22921799999999 22.560217 00:15:19 226
2 22223 00:17:13 114.23135400000001 22.562166 114.255798 22.590967000000003 00:29:06 713
3 22223 00:36:45 114.240196 22.56365 114.119965 22.566668 00:54:42 1077
4 22223 01:01:14 114.13541399999998 22.575933 114.166748 22.608267 01:08:17 423
... ... ... ... ... ... ... ... ...
464712 36947 22:08:22 113.914 22.5314 113.997 22.5456 22:36:53 1711
464713 36947 22:39:12 114.006 22.5481 113.996 22.5371 22:46:25 433
464714 36947 22:49:38 113.995 22.535 113.922 22.4965 23:13:15 1417
464715 36947 23:24:24 113.921 22.5135 113.93 22.4942 23:30:32 368
464716 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])
VehicleNum Stime SLng SLat ELng ELat Etime Duration order_time hour
0 22223 00:03:23 114.16746499999999 22.562468 114.22523500000001 22.55275 00:10:48 0 days 00:07:25 445 00
1 22223 00:11:33 114.22715 22.554167 114.22921799999999 22.560217 00:15:19 0 days 00:03:46 226 00
2 22223 00:17:13 114.23135400000001 22.562166 114.255798 22.590967000000003 00:29:06 0 days 00:11:53 713 00
3 22223 00:36:45 114.240196 22.56365 114.119965 22.566668 00:54:42 0 days 00:17:57 1077 00
4 22223 01:01:14 114.13541399999998 22.575933 114.166748 22.608267 01:08:17 0 days 00:07:03 423 01
... ... ... ... ... ... ... ... ... ... ...
464712 36947 22:08:22 113.914 22.5314 113.997 22.5456 22:36:53 0 days 00:28:31 1711 22
464713 36947 22:39:12 114.006 22.5481 113.996 22.5371 22:46:25 0 days 00:07:13 433 22
464714 36947 22:49:38 113.995 22.535 113.922 22.4965 23:13:15 0 days 00:23:37 1417 22
464715 36947 23:24:24 113.921 22.5135 113.93 22.4942 23:30:32 0 days 00:06:08 368 23
464716 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()

​

import matplotlib.pyplot as plt
fig     = plt.figure(1,(10,5),dpi = 250)
ax      = plt.subplot(111)
plt.sca(ax)#整理数据
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)
#绘制
plt.boxplot(datas)
#更改x轴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()

​

​

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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