Question

数据框有2个日期属于“对象”数据类型。 StartDate和EndDate的格式为mm / dd / yyyy。

  Name        StartDate          EndDate
  bou1        1/9/2017           1/10/2017
  bou2        12/31/2016         1/10/2017

输出：

  Name        StartDate          EndDate         Diff
  bou1        1/9/2017           1/10/2017       1
  bou2        12/31/2016         1/10/2017       10

任何建议将不胜感激！

Answer 1

您首先需要将这些列转换为日期时间，然后减去。

尝试

df['startDate'] = pd.to_datetime(df['startDate'])
df['EndDate'] = pd.to_datetime(df['EndDate'])
df['difInDate'] = (abs(df['startDate'].sub(df['EndDate'], axis = 0))) / np.timedelta64(1, 'D')
print(df['difInDate'])

abs只是为了使日子变得乐观，因为您是从小日期减去大日期或者，您也可以使用(df['EndDate'].sub(df['StartDate']

Answer 2

# Recreating your dataframe with dates stored as strings
df = pd.DataFrame({'Name'     : ['bou1', 'bou2'],               
                   'StartDate': ['01/09/2017','12/31/2016'],    
                   'EndDate'  : ['01/10/2017', '01/10/2017']}) 

# Date strings converted with pd.Datetime
df['StartDate'] = pd.to_datetime(df['StartDate'])               
df['EndDate'] = pd.to_datetime(df['EndDate'])

# .dt handles your calculation and .days outputs in days
df['Diff'] = (df['EndDate'] - df['StartDate']).dt.days          

# Just prints the columns in your order
df[['Name', 'StartDate', 'EndDate', 'Diff']]

两个日期之间的差异是数据框中的对象

2 个答案: