使用 dfply @dfpipe

编程问答 2022-05-10

问题描述

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中的计数，我可以找到以下内容：

索引 工作 计数
0 广告。 478
1 蓝领 946
2 企业家 168
3 女佣 112
4 管理 969
5 退休 230
6 个体经营者 183
7 服务 417
8 学生 84
9 技术员。 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、平衡、住房、贷款、联系、天、月、持续时间、活动、pdays、前一个、poutcome、y 30，失业，已婚，小学，没有，1787，没有，没有，蜂窝，19，十月，79，1，-1，0，未知，没有 33,服务,已婚,中学,没有,4789,是,蜂窝,11,5月,220,1,339,4,失败,没有 35,management,single,tertiary,no,1350,yes,16,apr,185,330,failure,no

我的目的是创建一个小函数，我也可以将其用于其他列，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,**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 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,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。

解决方法

Shameek Mukherjee，这是对示例代码的正确解释和缩进吗？除了缩进，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)
,

感谢提供示例数据。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，这导致了错误 "AttributeError:" DataFrame "object has no" variable "attribute " "

@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

如果你不喜欢熊猫烟斗，还有另一种形式：

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

   marital  COUNT
0  married      2
1   single      1

或者如果您熟悉 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)

示例数据：

>> 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
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