python - 在 Pandas 数据框中查找工作日组的平均值

Question

我的数据集是这样的:

         tripduration           starttime   User Type
0                 732   7/1/2015 00:00:03  Subscriber
1                 322   7/1/2015 00:00:06  Subscriber
2                 790   7/1/2015 00:00:17  Subscriber
3                1228   7/1/2015 00:00:23  Subscriber
4                1383   7/1/2015 00:00:44  Subscriber
5                 603   7/1/2015 00:01:00  Subscriber
6                 520   7/1/2015 00:01:03  Subscriber
7                 289   7/1/2015 00:01:06  Subscriber
8                1771   7/1/2015 00:01:25    Customer
9                 813   7/1/2015 00:01:41  Subscriber
10               1735   7/1/2015 00:01:50    Customer
11                832   7/1/2015 00:01:58  Subscriber
12               1210   7/1/2015 00:02:06  Subscriber
13                746   7/1/2015 00:02:07  Subscriber
14                749   7/1/2015 00:02:26  Subscriber
15                463   7/1/2015 00:02:26  Subscriber
16                331   7/1/2015 00:02:35  Subscriber
17                951   7/1/2015 00:02:43    Customer
18               1352   7/1/2015 00:02:47    Customer
19                275   7/1/2015 00:02:47  Subscriber
20                199   7/1/2015 00:03:05  Subscriber
21                383   7/1/2015 00:03:16    Customer
22               4210   7/1/2015 00:03:27  Subscriber
23                584   7/1/2015 00:03:34  Subscriber
24                735   7/1/2015 00:03:48  Subscriber
25                827   7/1/2015 00:03:56  Subscriber
26                677   7/1/2015 00:03:57  Subscriber
27               2371   7/1/2015 00:03:58    Customer
28                666   7/1/2015 00:04:03  Subscriber
29                999   7/1/2015 00:04:17  Subscriber
...               ...                 ...         ...
1085646           243  7/31/2015 23:57:25  Subscriber
1085647          1378  7/31/2015 23:57:29    Customer
1085648           230  7/31/2015 23:57:32  Subscriber
1085649          1669  7/31/2015 23:57:33  Subscriber
1085650           493  7/31/2015 23:57:44  Subscriber
1085651           822  7/31/2015 23:57:54  Subscriber
1085652           617  7/31/2015 23:58:03  Subscriber
1085653           349  7/31/2015 23:58:08  Subscriber
1085654           818  7/31/2015 23:58:12    Customer
1085655          2062  7/31/2015 23:58:15  Subscriber
1085656           945  7/31/2015 23:58:18    Customer
1085657           346  7/31/2015 23:58:24  Subscriber
1085658           399  7/31/2015 23:58:27  Subscriber
1085659           641  7/31/2015 23:58:42  Subscriber
1085660          1872  7/31/2015 23:58:43  Subscriber
1085661         12065  7/31/2015 23:58:51    Customer
1085662           265  7/31/2015 23:58:53  Subscriber
1085663           936  7/31/2015 23:58:58  Subscriber
1085664           395  7/31/2015 23:59:04  Subscriber
1085665           238  7/31/2015 23:59:10  Subscriber
1085666           551  7/31/2015 23:59:24  Subscriber
1085667           423  7/31/2015 23:59:23    Customer
1085668          1623  7/31/2015 23:59:24  Subscriber
1085669          1632  7/31/2015 23:59:24  Subscriber
1085670           305  7/31/2015 23:59:38  Subscriber
1085671           275  7/31/2015 23:59:40  Subscriber
1085672           530  7/31/2015 23:59:41  Subscriber
1085673           273  7/31/2015 23:59:42    Customer
1085674          1273  7/31/2015 23:59:56  Subscriber
1085675          1667  7/31/2015 23:59:59  Subscriber

我的问题

订户在任何工作日(周一至周五)的平均旅行时间是多少？

我的代码

函数 a4() 应该返回平均值( float 到两位小数):

def a4(rides):
    df1 = rides[rides['User Type'] == 'Subscriber']
    df1['starttime'] = df1['starttime'].apply(pd.to_datetime) #convert obect into datetime

我被困在这里获取工作日(周一至周五)来计算 tripduration 的平均值。我尝试使用 parser.parse(df1['starttime']) 解析 starttime 但出现错误:

TypeError: Parser must be a string or character stream, not Series

获取工作日平均值的正确方法是什么？

Answer 1

我认为你需要先转换 to_datetime 开始时间列。

然后按boolean indexing过滤.

如果所有 workday 都需要一个标量值，请使用 loc 来选择具有 mean 的列:

def a4(rides):
    rides['starttime'] = pd.to_datetime(rides['starttime'])
    m = (rides['starttime'].dt.dayofweek < 5) & (rides['User Type'] == 'Subscriber')
    return round(rides.loc[m, 'tripduration'].mean(), 2)

print (a4(rides))
825.33

如果需要每天单独添加新条件 dayofweek然后 groupby聚合 mean:

def a4(rides):
    rides['starttime'] = pd.to_datetime(rides['starttime'])
    df1 = rides[(rides['User Type'] == 'Subscriber') & (rides['starttime'].dt.dayofweek < 5)]
    return df1.groupby(df1['starttime'].dt.dayofweek)['tripduration'].mean().round(2)

print (a4(rides))
starttime
2    840.96
4    809.71
Name: tripduration, dtype: float64

如果不需要天数，请使用 weekday_name :

def a4(rides):
    rides['starttime'] = pd.to_datetime(rides['starttime'])
    df1 = rides[(rides['User Type'] == 'Subscriber') & (rides['starttime'].dt.dayofweek < 5)]
    return df1.groupby(df1['starttime'].dt.weekday_name)['tripduration'].mean().round(2)

print (a4(rides))
starttime
Friday       809.71
Wednesday    840.96
Name: tripduration, dtype: float64