python – 在列表中的值的不同列标题中打印值

2019年8月4日 178次阅读

此代码用于跟踪哪些交付延迟.我希望找到延迟交货的每个实例,并找到与之关联的采购订单编号.我当前的代码能够生成一个列表,显示指定范围的延迟天数.但是,由于这些值存储在列表中,因此无法找到与后期相关的采购订单编号.我希望在终端打印,采购订单号和交货延迟的天数. (从那里我将使用if语句仅查看值> 0以仅查看哪些交付延迟).我的问题是,我如何在终端上打印,采购订单编号及其旁边的天数(我不知道如何执行此操作,因为所有“迟到天数”的值都存储在列表)

import csv
import pandas as pd
import datetime


def calculate(number):   
    fileread = pd.read_csv('otd.csv', encoding='latin-1')
    Deliveryvalue = fileread['Delivery Date']
    Desiredvalue = fileread['source desired delivery date']



    date_format = '%m/%d/%Y'

    date1 = datetime.datetime.strptime(Deliveryvalue[number], date_format)
    date2 = datetime.datetime.strptime(Desiredvalue[number], date_format)

    diff= date1 - date2
    diff2 = diff.days



    return diff2

list = [] 
for i in range(1,20):
    list.append(calculate(i))

for y in list: 
    if y > 1:
        print(list)

打印这个：

[0, 0, 0, 0, 0, 0, 0, 0, -7, 3, 50, 0, 0, 0, 0, 0, 1, -9, 0]
# the negative numbers are early deliveries

这是我的csv文件的一个虚拟示例：

《python – 在列表中的值的不同列标题中打印值》

最佳答案

import pandas as pd

# change names appropriately
PURCHASE_ORDER = 'Purchase Order'
DELIVERY_DATE = 'Delivery Date'
DESIRED_DATE = 'Desired Date'
DELAYED_DAYS = 'Delayed Days'

df = pd.read_csv('otd.csv', index_col=PURCHASE_ORDER)

–

>> df
                  Delivery Date Desired Date
Purchase Order
001               2014-12-31   2014-12-31
002               2014-12-31   2014-12-31
003               2015-01-05   2015-01-05
004               2015-01-05   2015-01-05
005               2015-02-12   2015-02-11
006               2016-02-13   2016-02-11

最后两次送货迟到了.

df[DELIVERY_DATE] = pd.to_datetime(df[DELIVERY_DATE])
df[DESIRED_DATE] = pd.to_datetime(df[DESIRED_DATE])
df[DELAYED_DAYS] = df[DELIVERY_DATE] - df[DESIRED_DATE]
late_threshold = pd.Timedelta(days=0)
late_deliveries = df[DELAYED_DAYS] > late_threshold

–

>> df[late_deliveries].drop([DELIVERY_DATE, DESIRED_DATE], axis=1)

                     Delayed Days
Purchase Order             
005                  1 days
006                  2 days
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