如何修复“TypeError:sequence item 0:预期str实例，找到float”

Question

我尝试使用groupby方法组合dataframe列中的单元格值（字符串），使用逗号分隔分组单元格中的单元格值。我遇到了以下错误：

TypeError: sequence item 0: expected str instance, float found

错误发生在以下代码行，有关完整代码，请参阅代码块：

^{pr2}$

在groupby函数中，与未分组的dataframe中的每一行相对应的索引在联接之前自动添加到字符串中。这会导致类型错误。但是，我不知道如何解决这个问题。我浏览了很多帖子，但没有找到解决办法。如果有任何指导或帮助，我将不胜感激！在

# Import Necessary Libraries

import numpy as np
import pandas as pd
from bs4 import BeautifulSoup
import requests

# Use BeautifulSoup to scrap information in the table from the Wikipedia page, and set up the dataframe containing all the information in the table

wiki_html = requests.get('https://en.wikipedia.org/wiki/List_of_postal_codes_of_Canada:_M').text
soup = BeautifulSoup(wiki_html, 'lxml')
# print(soup.prettify())
table = soup.find('table', class_='wikitable sortable')
table_columns = []
for th_txt in table.tbody.findAll('th'):
    table_columns.append(th_txt.text.rstrip('\n'))

toronto_df = pd.DataFrame(columns=table_columns) 

for row in table.tbody.findAll('tr')[1:]:
    row_data = []
    for td_txt in row.findAll('td'):
        row_data.append(td_txt.text.rstrip('\n'))
    toronto_df = toronto_df.append({table_columns[0]: row_data[0],
                                    table_columns[1]: row_data[1],
                                    table_columns[2]: row_data[2]}, ignore_index=True)
toronto_df.head()

# Remove cells with a borough that is Not assigned
toronto_df.replace('Not assigned',np.nan, inplace=True)
toronto_df = toronto_df[toronto_df['Borough'].notnull()]
toronto_df.reset_index(drop=True, inplace=True)
toronto_df.head()

# If a cell has a borough but a Not assigned neighborhood, then the neighborhood will be the same as the borough
toronto_df['Neighbourhood'] = toronto_df.groupby(['Postcode','Borough'])['Neighbourhood'].agg(lambda x: ','.join(x))
toronto_df.drop_duplicates(inplace=True)
toronto_df.head()

“neighbour”列的预期结果应该使用逗号分隔分组单元格中的单元格值，显示如下内容（我还不能发布图像，所以我只提供链接）：

https://d3c33hcgiwev3.cloudfront.net/imageAssetProxy.v1/7JXaz3NNEeiMwApe4i-fLg_40e690ae0e927abda2d4bde7d94ed133_Screen-Shot-2018-06-18-at-7.17.57-PM.png?expiry=1557273600000&hmac=936wN3okNJ1UTDA6rOpQqwELESvqgScu08_Spai0aQQ

Answer 1

如注释中所述，NaN是一个浮点，因此尝试对其执行字符串操作是行不通的（这就是出现错误消息的原因）

将代码的最后一部分替换为： 根据您在注释中指定的逻辑，使用布尔索引来填充nan

# If a cell has a borough but a Not assigned neighborhood, then the neighborhood will be the same as the borough
toronto_df.Neighbourhood = np.where(toronto_df.Neighbourhood.isnull(),toronto_df.Borough,toronto_df.Neighbourhood)
toronto_df['Neighbourhood'] = toronto_df.groupby(['Postcode','Borough'])['Neighbourhood'].agg(lambda x: ','.join(x))