写入CSV文件时行未过滤

Question

此代码用于查找特定时间范围内的延迟交货（在此示例中为2018年），并将数据写入csv文件（otdedit.csv）。但是，尽管按年正确过滤了数据，但不是迟交的值也不会被过滤掉。我的问题是，如何过滤仅将延迟交货的行写入CSV文件otdedit.csv。

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的行仍会出现。

（此外，我也不知道为什么该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了（我已经隐藏了快照）

如果需要，这也是示例数据：

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

Answer 1

行

java.lang.NoSuchMethodException

正在将视图的副本创建到原始数据框中，并删除给定的列，但是您并未将此副本分配给任何对象。原始数据帧defaultValue不变。

创建df2后可以执行的操作是：

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