pandas -'dataframe'对象没有属性'str' [英] pandas - 'dataframe' object has no attribute 'str'

问题描述

我正在尝试过滤出包含产品列表的数据框.但是，我遇到了熊猫-每当我运行代码时，"dataframe"对象都没有属性"str"错误.

I am trying to filter out the dataframe that contains a list of product. However, I am getting the pandas - 'dataframe' object has no attribute 'str' error whenever I run the code.

这是代码行:

include_clique = log_df.loc[log_df['Product'].str.contains("Product A")]

如果有人有任何建议的想法，请告诉我.我已经搜索了很多次，而且非常困惑.

If anyone has any ideas of suggestions, please let me know. I've searched many times and I'm quite stuck.

Product是对象数据类型.

Product is an object datatype.

import __future__
import os
import pandas as pd
import numpy as np
import tensorflow as tf
import math



data = pd.read_csv("FILE.csv", header = None)

headerName=["DRID","Product","M24","M23","M22","M21","M20","M19","M18","M17","M16","M15","M14","M13","M12","M11","M10","M9","M8","M7","M6","M5","M4","M3","M2","M1"] 
cliques = [(Confidential)] 
data.columns=[headerName]


log_df = data

log_df = np.log(1+data[["M24","M23","M22","M21","M20","M19","M18","M17","M16","M15","M14","M13","M12","M11","M10","M9","M8","M7","M6","M5","M4","M3","M2","M1"]])
copy = data[["DRID","Product"]].copy()
log_df = copy.join(log_df)


include_clique = log_df.loc[log_df['Product'].str.contains("Product A")]

这是头:

   ID    PRODUCT  M24      M23       M22     M21
0  123421  A  0.000000  0.000000  1.098612  0.0   
1  141840  A  0.693147  1.098612  0.000000  0.0   
2  212006  A  0.693147  0.000000  0.000000  0.0   
3  216097  A  1.098612  0.000000  0.000000  0.0   
4  219517  A  1.098612  0.693147  1.098612  0.0

edit 2:这里是print(data)，A是产品.当我将其打印出来时，看起来好像A不在类别产品下.

edit 2: here is print(data), A is the product. it looks like A is not under the category product when I print it out.

     DRID                         Product   M24   M23  M22  M21  M20  \
0           52250  A                     0.0   0.0  2.0  0.0  0.0   
1          141840  A                    1.0   2.0  0.0  0.0  0.0   
2          212006  A                      1.0   0.0  0.0  0.0  0.0   
3          216097  A                      2.0   0.0  0.0  0.0  0.0   

推荐答案

简短答案:将data.columns=[headerName]更改为data.columns=headerName

说明::设置data.columns=[headerName]时，列为MultiIndex对象.因此，您的log_df['Product']是一个DataFrame，对于DataFrame，没有str属性.

Explanation: when you set data.columns=[headerName], the columns are MultiIndex object. Therefore, your log_df['Product'] is a DataFrame and for DataFrame, there is no str attribute.

设置data.columns=headerName时，log_df['Product']是单列，并且可以使用str属性.

When you set data.columns=headerName, your log_df['Product'] is a single column and you can use str attribute.

由于任何原因，如果需要将数据保留为MultiIndex对象，则还有另一种解决方案:首先将log_df['Product']转换为Series.之后，str属性可用.

For any reason, if you need to keep your data as MultiIndex object, there is another solution: first convert your log_df['Product'] into Series. After that, str attribute is available.

products = pd.Series(df.Product.values.flatten())
include_clique = products[products.str.contains("Product A")]

但是，我想第一个解决方案就是您要寻找的

However, I guess the first solution is what you're looking for

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