Python 如何修复AttributeError:';int';对象没有属性';条状';在熊猫中加载excel文件时
我试图在pandas中加载一个excel文件,但出现以下错误- AttributeError:“int”对象没有属性“strip” 为了便于理解,我从excel中取出了下面一行以及标题-Python 如何修复AttributeError:';int';对象没有属性';条状';在熊猫中加载excel文件时,python,python-3.x,pandas,dataframe,Python,Python 3.x,Pandas,Dataframe,我试图在pandas中加载一个excel文件,但出现以下错误- AttributeError:“int”对象没有属性“strip” 为了便于理解,我从excel中取出了下面一行以及标题- Row ID Order ID Order Date Ship Date Ship Mode Customer ID Customer Name Segment Country/Region City State Postal Code Region Product ID
Row ID Order ID Order Date Ship Date Ship Mode Customer ID Customer Name Segment Country/Region City State Postal Code Region Product ID Category Sub-Category Product Name Sales Quantity Discount Profit
1 CA-2018-152156 08-11-2018 11-11-2018 Second Class CG-12520 Claire Gute Consumer United States Henderson Kentucky 42420 NorthEAST FUR-BO-10001798 Finance Bookcases Bush Somerset Collection Bookcase 261.96 2 0 41.9136
这是全部代码-
local_path= '../../data/RetailStore.xlsx'
out_path= '../../out/hyperstore.csv'
def load_retail_data(local_path,sheet_name):
return pd.read_excel(
local_path,
header=4,
sheet_name=sheet_name,
parse_dates=True
)
def clean_headers(data_frame:pd.DataFrame) -> pd.DataFrame:
data_frame=data_frame.rename(columns=lambda x:x.strip())
data_frame=data_frame.rename(columns=lambda x:x.replace('\n',' '))
data_frame=data_frame.rename(columns=lambda x:x.replace("'",' '))
data_frame=data_frame.rename(columns=lambda x:x.replace(' ',' '))
return data_frame
def filter_ship_mode(df):
return df[(df[ColumnsStore.ship_mode]!= 'Standard Class') & (df[ColumnsStore.ship_mode]!='Second Class')]
def calc_retail_data(local_path,sheet_name):
retail_data=load_retail_data(local_path,sheet_name)
retail_clean_headers=clean_headers(retail_data)
retail_filtered=filter_ship_mode(retail_clean_headers)
return retail_filtered
if __name__=="__main__":
df_retail_data=calc_retail_data(local_path,'Orders')
df_retail_data.to_csv(out_path,index=False)
您可以将列标题类型转换为字符串
def clean_头(数据帧:pd.DataFrame)->pd.DataFrame:
df.columns=df.columns.astype(str)
data\u frame=data\u frame.rename(columns=lambda x:x.strip())
...
或者只是转义int类型
def clean_头(数据帧:pd.DataFrame)->pd.DataFrame:
df.columns=df.columns.astype(str)
data\u frame=data\u frame.rename(列=lambda x:x.strip(),如果是instance(x,str)else x)
#对其他收割台清洁功能执行相同操作。
...
col_dict=dict(zip(df.columns.values,[str(col.strip().replace('\n','')).replace('''','').replace(''),for col in list(df.columns.values)])->创建col dict,然后使用此dict重命名列我应该在代码中写这一行吗?上面的建议,基本上,您的问题是clean_headers
下的这一行:data_frame=data_frame.rename(columns=lambda x:x.strip())
-->您试图strip()
一个整数的x
值(例如,迭代列号,而不是名称)@Aelarion那么什么是正确的呢?