使用 dfply @dfpipe 创建函数时出错

Question

我有一个数据集“banks”，如果我对列名“jobs”进行分组以检查每个类别的计数，我可以找到以下内容：

index	jobs	count
0	adnin.	478
1	blue-collar	946
2	entrepreneur	168
3	housemaid	112
4	management	969
5	retired	230
6	self-employed	183
7	services	417
8	student	84
9	technician.	768

我还添加了我正在使用的数据集的前 3 行： 年龄、工作、婚姻、教育、默认、余额、住房、贷款、联系人、一天、一个月、持续时间、活动、pdays、上一个、poutcome、y 30,unused,married,primary,no,1787,no,no,cellular,19,oct,79,1,-1,0,unknown,no 33,services,married,secondary,no,4789,yes,yes,cellular,11,may,220,1,339,4,failure,no 35,management,single,tertiary,no,1350,yes,no,cellular,16,apr,185,1,330,1,failure,no

我的目的是创建一个可以用于其他列的小函数，因此我尝试使用“dfply”包创建一个函数。

import pandas as pd
import dfply
from dfply import *

#creating the function

@dfpipe
def woe_iv(df,variable):
    step1=df>>group_by(X.variable)>>summarize(COUNT=X.variable.count())
    return step1

#invoking the function

banks>>woe_iv(X.job)

但是，这段代码给了我一个错误，说明如下：

@dfpipe

def woe_iv(df,variable):
            
            step1=df>>group_by(X.variable)>>summarize(COUNT=X.variable.count())
            return step1
banks>>woe_iv(X.job)
Traceback (most recent call last):

  File "<ipython-input-46-d851aeac1927>", line 7, in <module>
    banks>>woe_iv(X.job)

  File "/opt/anaconda3/lib/python3.8/site-packages/dfply/base.py", line 142, in __rrshift__
    result = self.function(other_copy)

  File "/opt/anaconda3/lib/python3.8/site-packages/dfply/base.py", line 149, in <lambda>
    return pipe(lambda x: self.function(x, *args, **kwargs))

  File "/opt/anaconda3/lib/python3.8/site-packages/dfply/base.py", line 329, in __call__
    return self.function(*args, **kwargs)

  File "/opt/anaconda3/lib/python3.8/site-packages/dfply/base.py", line 282, in __call__
    return self.function(df, *args, **kwargs)

  File "<ipython-input-46-d851aeac1927>", line 5, in woe_iv
    step1=df>>group_by(X.variable)>>summarize(COUNT=X.variable.count())

  File "/opt/anaconda3/lib/python3.8/site-packages/dfply/base.py", line 142, in __rrshift__
    result = self.function(other_copy)

  File "/opt/anaconda3/lib/python3.8/site-packages/dfply/base.py", line 149, in <lambda>
    return pipe(lambda x: self.function(x, *args, **kwargs))

  File "/opt/anaconda3/lib/python3.8/site-packages/dfply/base.py", line 279, in __call__
    args = self._recursive_arg_eval(df, args[1:])

  File "/opt/anaconda3/lib/python3.8/site-packages/dfply/base.py", line 241, in _recursive_arg_eval
    return [

  File "/opt/anaconda3/lib/python3.8/site-packages/dfply/base.py", line 242, in <listcomp>
    self._symbolic_to_label(df, a) if i in eval_as_label

  File "/opt/anaconda3/lib/python3.8/site-packages/dfply/base.py", line 231, in _symbolic_to_label
    return self._evaluator_loop(df, arg, self._evaluate_label)

  File "/opt/anaconda3/lib/python3.8/site-packages/dfply/base.py", line 225, in _evaluator_loop
    return eval_func(df, arg)

  File "/opt/anaconda3/lib/python3.8/site-packages/dfply/base.py", line 181, in _evaluate_label
    arg = self._evaluate(df, arg)

  File "/opt/anaconda3/lib/python3.8/site-packages/dfply/base.py", line 175, in _evaluate
    arg = arg.evaluate(df)

  File "/opt/anaconda3/lib/python3.8/site-packages/dfply/base.py", line 71, in evaluate
    return self.function(context)

  File "/opt/anaconda3/lib/python3.8/site-packages/dfply/base.py", line 74, in <lambda>
    return Intention(lambda x: getattr(self.function(x), attribute),

  File "/opt/anaconda3/lib/python3.8/site-packages/pandas/core/generic.py", line 5139, in __getattr__
    return object.__getattribute__(self, name)

AttributeError: 'DataFrame' object has no attribute 'variable'

如果我遗漏了什么，请告诉我。

Answer 1

感谢您提供示例数据。问题的根本原因是您忘记在woe_iv()（即X[variable]）中的变量周围加上括号，导致错误“AttributeError：”DataFrame“object has no”variable“attribute”“ em>

@dfpipe
def woe_iv(df, variable):
    return df >> group_by(X[variable]) >> summarize(COUNT=X[variable].count())

banks = pd.read_excel('banks.xlsx')

>> print(banks >> woe_iv('marital'))

   marital  COUNT
0  married      2
1   single      1

如果你不喜欢 panda 管道，还有另一种形式：

>> banks.groupby(['marital']).size().reset_index(name='COUNT')

   marital  COUNT
0  married      2
1   single      1

如果您熟悉 SQL，请使用 PandaSQL：

SQL_Query = pd.read_sql_query(
'''select product_name, product_price_per_unit, units_ordered,
   ((units_ordered) * (product_price_per_unit)) AS revenue
   from tracking_sales''', conn)

样本数据：

>> print(banks)

   age         job  marital  education default  balance housing loan  \
0   30  unemployed  married    primary      no     1787      no   no   
1   33    services  married  secondary      no     4789     yes  yes   
2   35  management   single   tertiary      no     1350     yes   no   

    contact  day month  duration  campaign  pdays  previous poutcome   y
0  cellular   19   oct        79         1     -1         0  unknown  no  
1  cellular   11   may       220         1    339         4  failure  no  
2  cellular   16   apr       185         1    330         1  failure  no

Answer 2

Shameek Mukherjee，这是对您的示例代码的正确解释和缩进吗？除了缩进之外，我找不到任何区别。

import dfply
from dfply import *

@dfpipe
def woe_iv(df,variable):
    step1 = df>>group_by(X.variable)>>summarize(COUNT=X.variable.count())
    return step1

banks>>woe_iv(X.job)

第二个例子：

@dfpipe
def woe_iv(df,variable):
    step1 = df>>group_by(X.variable)>>summarize(COUNT=X.variable.count())
    return step1

banks>>woe_iv(X.job)