【发布时间】:2018-08-30 18:39:00
【问题描述】:
此代码用于查找特定时间范围内的延迟交货(在本示例中为 2018 年)并将数据写入 csv 文件 (otdedit.csv)。但是,尽管数据按年份正确过滤,但未过滤掉未延迟交付的值。我的问题是,我如何过滤掉只有延迟交付才能写入 csv 文件 otdedit.csv 的行。
import pandas as pd
from datetime import datetime
from datetime import timedelta
PURCHASE_ORDER = 'Material'
DELIVERY_DATE = 'Delivery Date'
DESIRED_DATE = 'Desired Delivery'
DELAYED_DAYS = 'Delayed Days'
df = pd.read_csv('otd.csv', index_col=PURCHASE_ORDER)
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)
df['Delivery Date'] = pd.to_datetime(df['Delivery Date'], format='%m/%d/%Y')
df['Desired Delivery'] = pd.to_datetime(df['Desired Delivery'], format='%m/%d/%Y')
df2 = df[(df['Delivery Date'].dt.year >= 2018) & (df['Delivery Date'].dt.year <= 2018)]
df2['Diff Deliv Date'] = df2['Delivery Date'] - df2['Desired Delivery']
df2.to_csv('otdedit.csv', sep=',')
这是 otdedit.csv 的快照,请注意延迟天数为 0 的行仍然出现。
(另外作为旁注,我不知道为什么这个程序也没有按标题过滤,我只希望出现这 4 列,但是原始文件中的每一列都显示(我已经隐藏了这些列快照)
如果需要,这里还有示例数据:
Material Delivery Date Desired Delivery Delayed Days Diff Deliv Date
20030650 1/3/2018 12/22/2017 12 days 00:00:00.000 12 days 00:00:00.00000
20056352 1/2/2018 12/31/2017 2 days 00:00:00.00000 2 days 00:00:00.000000
20052196 10/18/2018 10/18/2018 0 days 00:00:00.0000 0 days 00:00:00.0000000
20031687 1/3/2018 12/27/2017 7 days 00:00:00.0000 7 days 00:00:00.000000
20031687 2/3/2018 2/3/2018 0 days 00:00:00.00000 0 days 00:00:00.000000
20056053 5/14/2018 3/11/2017 429 days 00:00:00.00 429 days 00:00:00.0000000
20070547 1/2/2018 8/15/2017 140 days 00:00:00.0000 140 days 00:00:00.00
【问题讨论】:
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嘿,你能给我们提供csv格式的示例数据还是使用
df2.to_dict()的输出?
标签: python pandas csv datetime export-to-csv