我正在尝试过滤出包含产品列表的数据框。但是，我得到的熊猫-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。
产品是对象数据类型。
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
编辑2：这是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
答案很简单：改变data.columns=[headerName]成data.columns=headerName
说明：设置时data.columns=[headerName]，列为MultiIndex对象。因此，您log_df['Product']是一个DataFrame，对于DataFrame，没有str属性。
设置时data.columns=headerName，您log_df['Product']只有一列，可以使用strattribute。
出于任何原因，如果需要将数据保留为MultiIndex对象，则还有另一种解决方案：首先将您的数据转换log_df['Product']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
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我来说两句