python - 函数内 Beautiful Soup 中的“ResultSet”对象没有属性 'findAll' 错误消息

Question

我正在学习 Pyhton，尤其是 beautiful soup，并且我正在使用一组 html 文件进行正则表达式的 Google 练习，其中包含不同年份的流行婴儿名字(例如baby1990.html 等)。如果您有兴趣，可以在这里找到此数据集:https://developers.google.com/edu/python/exercises/baby-names

每个 html 文件都包含一个包含婴儿姓名数据的表格，如下所示:

我编写了一个函数，从 html 文件中提取婴儿的名字并将它们存储到数据帧中，字典中的数据帧以及聚合在单个数据帧中的所有数据帧。

每个 html 文件中有两个表。包含婴儿数据的表具有以下 html 代码:

<table width="100%" border="0" cellspacing="0" cellpadding="4" summary="formatting">

在这一行中，独特的属性是summary =“formatting”。

我编写的函数是根据我收到的反馈进行编辑的，如下:

def babynames(path):

# This function takes the path of the directory where the html files are stored and returns a list containing the 
# a dataframe which encompasses all the tabular baby-names data in the files and as well as a dictionary holding
# a separate dataframe for each html file

# 0: Initialize objects
dicnames = {}  # will hold the dataframes containing the tabular data of each year
dfnames = pd.DataFrame([])  # will hold the aggregate data

# 1: Create a list containing the full paths of the baby files in the directory indicated by the path argument of the babynames
# function
allfiles = files(path)

# 2: Begin the looping through the files 

for file in allfiles: 
        with open(file,"r") as f: soup = bs(f.read(), 'lxml')  # Convert the file to a soup

        # 3. Initialize empty lists to hold the contents of the cells
        Rank=[]
        Baby_1 =[]
        Baby_2 =[] 
        df = pd.DataFrame([])

        # 4. Extract the Table containing the Baby data and loop through the rows of this table

        for row in soup.select("table[summary=formatting] tr"):

         # 5. Extract the cells 

            cells = row.findAll("td")

            # 6. Convert to text and append to lists
            try:
                Rank.append(cells[0].find(text=True))  
                Baby_1.append(cells[1].find(text=True))
                Baby_2.append(cells[2].find(text=True))
            except:
                print "file: " , file
                try:
                        print "cells[0]: " , cells[0]
                except:
                        print "cells[0] : NaN"
                try:
                        print "cells[1]: " , cells[1]
                except:
                        print "cells[1] : NaN"    
                try:
                        print "cells[2]: " , cells[2]
                except:
                        print "cells[2] : NaN"   

            # 7. Append the lists to the empty dataframe df
            df["Rank"] = Rank 
            df["Baby_1"] = Baby_1
            df["Baby_2"] = Baby_2

            # 8. Append the year to the dataframe as a separate column
            df["Year"] = extractyear(file)  # Call the function extractyear() defined in the environment with input
                                            # the full pathname stored in variable file and examined in the current
                                            # iteration

            # 9. Rearrange the order of columns
            # df.columns.tolist() = ['Year', 'Rank', 'Baby_1', 'Baby_2']

            #10. Store the dataframe to a dictionary as the value which key is the name of the file
            pattern = re.compile(r'.*(baby\d\d\d\d).*')
            filename = re.search(pattern, file).group(1)
            dicnames[filename] = df

    # 11. Combine the dataframes stored in the dictionary dicname to an aggregate dataframe dfnames
        for key, value in dicnames.iteritems():
             dfnames = pd.concat[dfnames, value] 

    # 12. Store the dfnames and dicname in a list called result.  Return result.
        result = [dfnames, dicnames]
        return result

当我使用给定路径(存储 html 文件的目录的路径)运行该函数时，我收到以下错误消息:

result = babynames(path)

输出:

---------------------------------------------------------------------------


file:  C:/Users/ALEX/MyFiles/JUPYTER NOTEBOOKS/google-python-exercises/babynames/baby1990.html
cells[0]:  cells[0] : NaN
cells[1]:  cells[1] : NaN
cells[2]:  cells[2] : NaN
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-72-5c9ebdc4dcdb> in <module>()
----> 1 result = babynames(path)

<ipython-input-71-a0263a6790da> in babynames(path)
     54 
     55                 # 7. Append the lists to the empty dataframe df
---> 56                 df["Rank"] = Rank
     57                 df["Baby_1"] = Baby_1
     58                 df["Baby_2"] = Baby_2

C:\users\alex\Anaconda2\lib\site-packages\pandas\core\frame.pyc in __setitem__(self, key, value)
   2355         else:
   2356             # set column
-> 2357             self._set_item(key, value)
   2358 
   2359     def _setitem_slice(self, key, value):

C:\users\alex\Anaconda2\lib\site-packages\pandas\core\frame.pyc in _set_item(self, key, value)
   2421 
   2422         self._ensure_valid_index(value)
-> 2423         value = self._sanitize_column(key, value)
   2424         NDFrame._set_item(self, key, value)
   2425 

C:\users\alex\Anaconda2\lib\site-packages\pandas\core\frame.pyc in _sanitize_column(self, key, value)
   2576 
   2577             # turn me into an ndarray
-> 2578             value = _sanitize_index(value, self.index, copy=False)
   2579             if not isinstance(value, (np.ndarray, Index)):
   2580                 if isinstance(value, list) and len(value) > 0:

C:\users\alex\Anaconda2\lib\site-packages\pandas\core\series.pyc in _sanitize_index(data, index, copy)
   2768 
   2769     if len(data) != len(index):
-> 2770         raise ValueError('Length of values does not match length of ' 'index')
   2771 
   2772     if isinstance(data, PeriodIndex):

ValueError: Length of values does not match length of index

细胞[0]，细胞1并且 cells[2] 应该有值。

正如我提到的，前面还有一个表由以下 html 代码标识:

<table width="100%" border="0" cellspacing="0" cellpadding="4">

我运行了一个没有指定表的函数版本——我没有观察到 html 文件中有两个表。在那个版本中我没有遇到这种类型的错误。我在第 6 行收到了错误消息，指出 try 语句的标识不正确——我不明白这一点——并且在第 9 行收到错误消息，我试图重新排列数据帧的列——我也无法理解。/p>

我们将不胜感激您的建议。

Answer 1

right_table 是一个 ResultSet 实例(基本上是表示元素的 Tag 实例的列表)，它没有 findAll( ) 或 find_all() 方法。

相反，如果您有多个元素，则可以循环遍历 right_table 中的元素:

right_table = soup.find_all("table", summary_ = "formatting")

for table in right_table:
    for row in table.findAll("tr"):
        # ...

或者，如果只有一个，请使用 find():

right_table = soup.find("table", summary_ = "formatting")

或者，使用单个 CSS 选择器:

for row in soup.select("table[summary=formatting] tr"):
    # ...