Question

更新。我已将数据合并到多维列表中，如图所示

[('Medical Services', 2), ('Medical Services', 2), ('Physical Therapy', 5), 
 ('Physical Therapy', 1), ('Chiropractic', 0)]

是否可以按如下方式获得结果

 The average response time for Medical Services is 2 days

（请注意，它应删除重复项）

 The average response time for Physical Therapy is 5 days

（请注意，有两种物理疗法，但我从它开始的最长天数为5）

 The average response time for Chiropractic is less than 24 hours

（请注意，如果是0天，则应更改为“少于24小时”）

Answer 1

这是一个非常简单的解决方案，没有任何外部库：

data = [('Medical Services', 2), ('Medical Services', 2), ('Physical Therapy', 5), ('Physical Therapy', 1), ('Chiropractic', 0)]

from collections import defaultdict
label2days = defaultdict(list)
for label, days in data:
    label2days[label].append(day2)
for label, days in label2days.items():
    average = sum(days) / len(days)
    print("The average response time for {0} is {1}".format(
        label,
        "%.2f" % average if average >= 1 else "less than 24 hours",
    ))

打印：

脊椎按摩疗法的平均反应时间少于24小时物理治疗的平均响应时间为3.00天医疗服务的平均响应时间为2.00天

Answer 2

[ 注意： 此答案旨在解决OP的原始问题，该问题后来经过修订。]

这可能不是你想要的timedelta，但我相信它很接近。

我建议您使用Pandas解决此问题。假设您的csv数据位于名为data.csv的文件中：

import pandas as pd

# load the data into a pandas dataframe
df = pd.read_csv('data.csv', header = None, names = ['Service', 'Reported Date', 'Completion Date', 'Days'])

# convert date strings to dates
df['Reported Date'] = pd.to_datetime(df['Reported Date'])
df['Completion Date'] = pd.to_datetime(df['Completion Date'])

# calculate the timedelta and add it to the 'Days' column
df['Days'] = (df['Completion Date'] - df['Reported Date'])

# convert the timedelta to an int
df['Days'] = df['Days'].dt.days

# print our dataframe
print(df)
print

# convert the timedelta 'Days' to days
new_df = df.groupby([df['Service']]).mean()

# print our new dataframe
print(new_df)
print

for row in new_df.itertuples():
    if row[1] < 1:
        print("The average response time for %s is %s days." % (row[0], row[1]))
    else:
        print("The average response time for %s is less than 24 hours." % (row[0]))

产生以下输出：

================================================================================
Oct 4, 2017, 9:00:40 AM
untitled text 11
--------------------------------------------------------------------------------
            Service       Reported Date     Completion Date  Days
0  Medical Services 2017-03-08 09:20:00 2017-03-12 14:59:00     4
1  Medical Services 2017-03-08 09:28:00 2017-03-12 14:59:00     4
2  Physical Therapy 2017-03-04 09:34:00 2017-03-14 19:21:00    10
3  Physical Therapy 2017-03-04 09:39:00 2017-03-14 15:00:00    10
4  Medical Services 2017-03-01 09:49:00 2017-03-24 19:21:00    23
5      Chiropractic 2017-03-27 10:41:00 2017-03-27 19:22:00     0
6  Medical Services 2017-03-02 10:46:00 2017-03-04 15:00:00     2
7      Chiropractic 2017-03-27 11:36:00 2017-03-27 12:51:00     0
8  Medical Services 2017-03-02 14:17:00 2017-03-02 19:22:00     0

                  Days
Service               
Chiropractic       0.0
Medical Services   6.6
Physical Therapy  10.0

The average response time for Chiropractic is less than 24 hours.
The average response time for Medical Services is 6.6 days.
The average response time for Physical Therapy is 10.0 days.

Pandas是一个非常强大的工具，可以很容易地执行这些操作。

<强>更新

虽然您仍需要使用外部模块进行日期时间计算，但此处仅使用日期时间。这个脚本很冗长，以便您可以看到正在发生的事情，但有几种方法可以合并许多步骤。

import datetime

data = []
services = []

with open('data.csv', 'r') as f:
    lines = f.readlines()

# construct list 'data' which contains the rows of data as lists
for line in lines:
    item = line.strip().split(',')
    data.append(item)

# construct list 'services' which contains a list of unique services
for item in data:
    if item[0] not in services:
        services.append(item[0])

# create a timedelta for each row, convert it to days and add it to the end of each row
for item in data:
    reported = datetime.datetime.strptime(item[1], '%m/%d/%Y %H:%M')
    delivered = datetime.datetime.strptime(item[2], '%m/%d/%Y %H:%M')
    item.append( (delivered-reported).total_seconds() )

for service in services:
    total_days = 0
    counter = 0

    for row in data:
        if service in row:
            total_days += row[3]
            counter += 1

    average_days = (total_days / counter) / 86400

    if average_days < 1:
        print("The average response time for %s is less than 24 hours." % (service))
    else:
        print("The average response time for %s is %.2f days." % (service, average_days))

输出：

================================================================================
Oct 4, 2017, 10:07:40 AM
untitled text 11
--------------------------------------------------------------------------------
The average response time for Medical Services is 6.85 days.
The average response time for Physical Therapy is 10.32 days.
The average response time for Chiropractic is less than 24 hours.

如何在多维列表python中操作元素

2 个答案: