Python + dataframe : AttributeError: 'float' object has no attribute 'replace'

Question

我正在尝试编写一个函数来对 Pandas 数据框的指定列（描述，event_name）进行一些文本处理。我写了这段代码：

#removal of unreadable chars, unwanted spaces, words of at most length two from 'description' column and lowercase the 'description' column

def data_preprocessing(source):

    return source.replace('[^A-Za-z]',' ')
    #data['description'] = data['description'].str.replace('\W+',' ')
    return source.lower()
    return source.replace("\s\s+" , " ")
    return source.replace('\s+[a-z]{1,2}(?!\S)',' ')
    return source.replace("\s\s+" , " ")

data['description'] = data['description'].apply(lambda row: data_preprocessing(row))
data['event_name'] = data['event_name'].apply(lambda row: data_preprocessing(row))

出现以下错误：

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-94-cb5ec147833f> in <module>()
----> 1 data['description'] = data['description'].apply(lambda row: data_preprocessing(row))
      2 data['event_name'] = data['event_name'].apply(lambda row: data_preprocessing(row))
      3 
      4 #df['words']=df['words'].apply(lambda row: eliminate_space(row))
      5 

~/anaconda3/envs/tensorflow/lib/python3.5/site-packages/pandas/core/series.py in apply(self, func, convert_dtype, args, **kwds)
   2549             else:
   2550                 values = self.asobject
-> 2551                 mapped = lib.map_infer(values, f, convert=convert_dtype)
   2552 
   2553         if len(mapped) and isinstance(mapped[0], Series):

pandas/_libs/src/inference.pyx in pandas._libs.lib.map_infer()

<ipython-input-94-cb5ec147833f> in <lambda>(row)
----> 1 data['description'] = data['description'].apply(lambda row: data_preprocessing(row))
      2 data['event_name'] = data['event_name'].apply(lambda row: data_preprocessing(row))
      data['description'] = data['description'].str.replace('\W+',' ')    
<ipython-input-93-fdfec5f52a06> in data_preprocessing(source)
      3 def data_preprocessing(source):
      4 
----> 5     return source.replace('[^A-Za-z]',' ')
      6     #data['description'] = data['description'].str.replace('\W+',' ')
      7     source = source.lower()

AttributeError: 'float' object has no attribute 'replace'

如果我按照下面的方式编写代码，没有函数，它可以完美运行：

data['description'] = data['description'].str.replace('[^A-Za-z]',' ')

Answer 1

需要解决两件事：

首先，当你apply一个lambda函数到pandas系列时，lambda函数被应用到每个元素系列。我认为您需要的是以矢量化方式将您的函数应用于整个系列。

第二个，你的函数有多个return语句。结果，只有第一个语句 return source.replace('[^A-Za-z]',' ') 永远是运行。您需要做的是在函数内部对变量 source 进行预处理更改，最后 return 修改后的 source （或中间变量）在最后。

要重写您的函数以对整个 pandas 系列进行操作，请将每次出现的 source. 替换为 source.str.。新函数定义：

def data_preprocessing(source):
    source = source.str.replace('[^A-Za-z]',' ')
    #data['description'] = data['description'].str.replace('\W+',' ')
    source = source.str.lower()
    source = source.str.replace("\s\s+" , " ")
    source = source.str.replace('\s+[a-z]{1,2}(?!\S)',' ')
    source = source.str.replace("\s\s+" , " ")
    return source

然后，代替这个：

data['description'] = data['description'].apply(lambda row: data_preprocessing(row))
data['event_name'] = data['event_name'].apply(lambda row: data_preprocessing(row))

试试这个：

data['description'] = data_preprocessing(data['description'])
data['event_name'] = data_preprocessing(data['event_name'])

Python + dataframe : AttributeError: 'float' object has no attribute 'replace'

Python + dataframe : AttributeError: 'float' object has no attribute 'replace'

python

text-processing

dataframe

pandas