python – 通过应用第二个数据帧中的规则来更改数据帧

2023年4月6日 190次阅读

嗨,我有两个数据帧.

输入数据框架： –

id   number      idsc                 mfd 
738  as6812      *fage abc van brw    amz 
745  786-151     *glaeceau smt sp     amz 
759  b0nadum     ankush 574415 mo...  admz 
764  fdad3-al-c  lib anvest-al...     amz 
887  rec-2s-5    or abc sur...        c 
64   00954       ankush pure g...     amz 
8    0000686     dor must die         a 
3    000adf623   bsc test 10-pi...    amz

检查条件数据框： –

condition      destinationfield expression                                b_id          
True           idsc             [idsc].lower()                            1 
[mfd]=="amz"   idsc             re.sub(r'\abc\b','a',[idsc])              1 
[mfd]=="admz"  idsc             re.sub(r'and \d+ other item', '', [idsc]) 1 
True           idsc             re.sub(r'[^a-z0-9 ]',r'',[idsc])          1 
True           idsc             [idsc].strip()                            1 
[mfd] == "c"   idsc             re.sub(r'\ankush\b','ank',[idsc])         1 
True           number           re.sub(r'[^0-9]',r'',[number])            1
True           number           [number].strip()                          1

我正在寻找在输入数据帧上应用条件数据帧的每个规则并获得新的数据帧.

如果我的条件为真,那么我需要在所有行上应用它.如果除了true之外还有任何特定值,那么我需要将该条件应用于特定记录.

有没有更好的方法在pyspark中执行此操作,因为正则表达式与python相关.而不是在for循环中运行它.

id   number     idsc              mfd 
738  as6812     *fage a van brw   amz 
745  786-151    *glaeceau smt sp  amz 
759  b0nadum    ank 574415 mo...  admz 
764  fdad3-al-c lib anvest-al...  amz 
887  rec-2s-5   or a sur...       c 
64   00954      ank pure g...     amz 
8    0000686    dor must die      a 
3    000adf623  bsc test 10-pi... amz

输入数据管道分开

id| number|idsc|mfd 
738|as6812|*fage abc van brw|amz 
745|786-151|*glaeceau smt sp|amz 
759|b0nadum|ankush 574415 mo...|admz 
764|fdad3-al-c|lib anvest-al...|amz 
887|rec-2s-5|or abc sur...|c 
64| 00954|ankush pure g...|amz 
8|0000686|dor must die a 
3|000adf623|bsc test 10-pi...|amz

条件数据管道分开

条件| destinationfield |表达式| B_ID |

True|idsc|[idsc].lower()|1 
[mfd]=="amz"|idsc|re.sub(r'\abc\b','a',[idsc])|1 
[mfd]=="admz"|idsc|re.sub(r'and \d+ other item', '', [idsc])|1 
True|idsc|re.sub(r'[^a-z0-9 ]',r'',[idsc])|1 
True|idsc|[idsc].strip()|1 
[mfd] == "c"|idsc|re.sub(r'\ankush\b','ank',[idsc])|1 
True|number|re.sub(r'[^0-9]',r'',[number])|1
True|number|[number].strip()|1

谢谢,
安库什雷迪

最佳答案 您可以尝试使您的Condition Dataframe可评估.

如果它是可评估的,您可以在条件和表达式上调用eval().

def apply_condition(df, df_condition):
 # write a function get_df_evaluable_condition which both does
 # replace "[any_column]" by "df.['any_column']" in createcondition
 # replace "[destinationfield]" by "element" in expression

 df_evaluable_condition = get_df_evaluable_condition(df_evaluable_condition)

 for index, row in df_evaluable_condition.iterrows():
    createcondition = row['createcondition']
    destinationfield = row['destinationfield']
    expression = row['expression']
    # just apply expression where createcondition is true
    df.loc[eval(createcondition), destinationfield] = 
      df.loc[eval(createcondition), destinationfield].apply(lambda element: eval(expression))

顺便说一下,如果表达式包含对不是目标列的列的引用,则最后一行代码将不起作用.你需要更复杂的东西才能达到你想要的效果.

如果您不知道Condition Dataframe的样子,我建议不要使用此方法.不要在未知字符串上调用eval()！

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