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首页 > 解决方案 > 如何解决此“TypeError：序列项 0：预期的 str 实例，找到浮点数”

python - 如何解决此“TypeError：序列项 0：预期的 str 实例，找到浮点数”

问题描述

我正在尝试使用 groupby 方法组合数据框列中的单元格值（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，完整代码见代码块：

toronto_df['Neighbourhood'] = toronto_df.groupby(['Postcode','Borough'])['Neighbourhood'].agg(lambda x: ','.join(x))

似乎在groupby函数中，未分组数据框中每一行对应的索引在加入之前自动添加到字符串中。这会导致 TypeError。但是，我不知道如何解决这个问题。我浏览了很多线程，但没有找到解决方案。我将不胜感激任何指导或帮助！

# 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()

'Neighbourhood' 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（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

标签： pythonpython-3.xpandaspandas-groupby

解决方案

如评论中所述， theNaN是一个浮点数，因此尝试对其进行字符串操作不起作用（这就是错误消息的原因）

用以下代码替换您的最后一部分代码：根据您在评论中指定的逻辑，使用布尔索引完成 nan 的填充

# 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))

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