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Python – 如何检查 Pandas 中缺失的日期

2023-06-02 21:54:03 567

要检查丢失的日期，首先，让我们设置一个包含日期记录的列表字典，即我们的示例中的购买日期-

#列表字典
d = {'Car': ['BMW', 'Lexus', 'Audi', 'Mercedes', 'Jaguar', 'Bentley'],
   'Date_of_purchase': ['2020-10-10', '2020-10-12', '2020-10-17', '2020-10-16', '2020-10-19', '2020-10-22']}

现在，从上面的列表字典创建一个数据框-

dataFrame = pd.DataFrame(d)

接下来，将其设置为索引-

dataFrame = dataFrame.set_index('Date_of_purchase')

使用to_datetime()将字符串转换为DateTime对象-

dataFrame.index = pd.to_datetime(dataFrame.index)

显示范围内的剩余日期-

k = pd.date_range( start="2020-10-10", end="2020-10-22").difference(dataFrame.index);

示例

以下是代码-

import pandas as pd

#列表字典
d = {'Car': ['BMW', 'Lexus', 'Audi', 'Mercedes', 'Jaguar', 'Bentley'],
   'Date_of_purchase': ['2020-10-10', '2020-10-12', '2020-10-17', '2020-10-16', '2020-10-19', '2020-10-22'] }

#creatingdataframefromtheabovedictionaryoflists
dataFrame = pd.DataFrame(d)
print"DataFrame...\n",dataFrame

#Date_of_purchasesetasindex
dataFrame = dataFrame.set_index('Date_of_purchase')

#usingto_datetime()toconvertstringtoDateTimeobject
dataFrame.index = pd.to_datetime(dataFrame.index)

#remainingdatesdisplayedasoutput
print("\nDisplaying remaining dates from a range of dates...")
k = pd.date_range(start="2020-10-10", end="2020-10-22").difference(dataFrame.index);

print(k);

输出结果

这将产生以下输出-

DataFrame...
         Car    Date_of_purchase
0       BMW           2020-10-10
1     Lexus           2020-10-12
2      Audi           2020-10-17
3  Mercedes           2020-10-16
4    Jaguar           2020-10-19
5   Bentley           2020-10-22

Displaying remaining dates from a range of dates...
DatetimeIndex(['2020-10-11', '2020-10-13', '2020-10-14', '2020-10-15',
   '2020-10-18', '2020-10-20', '2020-10-21'],
   dtype='datetime64[ns]', freq=None)

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Python – 如何检查 Pandas 中缺失的日期

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