熊猫-'dataframe'对象没有属性'str'

时间:2018-07-24 15:18:31

标签: python pandas q

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。

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。

Product是对象数据类型。

编辑:

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。

     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   

1 个答案:

答案 0 :(得分:1)

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

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

设置data.columns=headerName时,您的log_df['Product']是一列,您可以使用str属性。

出于任何原因,如果您需要将数据保留为MultiIndex对象,则有另一种解决方案:首先将log_df['Product']转换为Series。之后,str属性可用。

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