如何使用python中的正则表达式检测数据框中的日期时间字段

Question

我正在尝试返回数据框中类型为 datetime 的字段，然后将字段名称替换为“date”，以便将 datetime 拆分为年份和月份。

当我运行代码时它崩溃并显示以下错误：

   df = df.rename(columns={converteddate[0]: 'date'})
UnboundLocalError: local variable 'converteddate' referenced before assignment

代码：

import pandas as pd

df = pd.DataFrame({'event_type': ['watch movie ', 'stay at home', 'swimming','camping','meeting'], 
               'date': ['8/11/2020', '2/13/2020', '7/04/2020','1/22/2020','7/28/2020'],
                'event_mohafaza':['loc1','loc3','loc2','loc5','loc4'],
                 ' number_person ':[24,39,20,10,33],})
        
non_numeric_cols = [col for col, col_type in df.dtypes.iteritems() if col_type == 'object']
if len(non_numeric_cols) > 0:
         mask = df.astype(str).apply(lambda x : x.str.match('[0-3]?[0-9]-[0-3]?[0-9]-(?:[0-9]{2})?[0-9]{2}$').any())
            
         if mask.any() == True:
               df.loc[:,mask] = df.loc[:,mask].apply(pd.to_datetime,dayfirst=False)
               converteddate = [col for col in df.columns if df[col].dtype == 'datetime64[ns]']
         df = df.rename(columns={converteddate[0]: 'date'})
         if "date" in df.columns:
               df['year_month'] = df['date'].map(lambda x: x.strftime('%Y/%m'))

Answer 1

如果你修改你的正则表达式匹配有效：

import pandas as pd

df = pd.DataFrame({'event_type': ['watch movie ', 'stay at home', 'swimming','camping','meeting'], 
               'date': ['8/11/2020', '2/13/2020', '7/04/2020','1/22/2020','7/28/2020'],
                'event_mohafaza':['loc1','loc3','loc2','loc5','loc4'],
                 ' number_person ':[24,39,20,10,33],})

print(df)
        
non_numeric_cols = [col for col, col_type in df.dtypes.iteritems() if col_type == 'object']
if len(non_numeric_cols) > 0:
    #mask = df.astype(str).apply(lambda x : x.str.match('[0-3]?[0-9]-[0-3]?[0-9]-(?:[0-9]{2})?[0-9]{2}$').any())
    mask = df.astype(str).apply(lambda x : x.str.match('^([1-9]|1[0-9]|2[0-9]|3[0-1])(.|-|/)([1-9]|1[0-2])(.|-|/)20[0-9][0-9]$').any())
            
    if mask.any() == True:
        df.loc[:,mask] = df.loc[:,mask].apply(pd.to_datetime,dayfirst=False)
        converteddate = [col for col in df.columns if df[col].dtype == 'datetime64[ns]']
    df = df.rename(columns={converteddate[0]: 'date'})
    if "date" in df.columns:
        df['year_month'] = df['date'].map(lambda x: x.strftime('%Y/%m'))
        
    print(df)

产生

     event_type       date event_mohafaza   number_person 
0  watch movie   8/11/2020           loc1               24
1  stay at home  2/13/2020           loc3               39
2      swimming  7/04/2020           loc2               20
3       camping  1/22/2020           loc5               10
4       meeting  7/28/2020           loc4               33
     event_type       date event_mohafaza   number_person  year_month
0  watch movie  2020-08-11           loc1               24    2020/08
1  stay at home 2020-02-13           loc3               39    2020/02
2      swimming 2020-07-04           loc2               20    2020/07
3       camping 2020-01-22           loc5               10    2020/01
4       meeting 2020-07-28           loc4               33    2020/07

您没有替换“日期”列，而是添加了“年月”列（我保持原样）。