Python 熊猫 - 'dataframe' 对象没有属性 'str'
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pandas - 'dataframe' object has no attribute 'str'
提问by David Luong
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.
我正在尝试过滤掉包含产品列表的数据框。但是，我得到了熊猫 - 每当我运行代码时，'dataframe' 对象都没有属性 'str' 错误。
Here is the line of code:
这是代码行：
include_clique = log_df.loc[log_df['Product'].str.contains("Product A")]
If anyone has any ideas of suggestions, please let me know. I've searched many times and I'm quite stuck.
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，但我很困惑。
Product is an object datatype.
产品是一种对象数据类型。
EDIT:
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")]
Here is the head:
这是头部：
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: here is print(data), A is the product. it looks like A is not under the category product when I print it out.
编辑 2：这里是打印（数据），A 是产品。当我打印出来时，它看起来 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
回答by hoang tran
Short answer:change data.columns=[headerName]into data.columns=headerName
答案很简单：改变data.columns=[headerName]成data.columns=headerName
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 strattribute.
说明：设置时data.columns=[headerName]，列是 MultiIndex 对象。因此，您log_df['Product']是一个 DataFrame，而对于 DataFrame，则没有str属性。
When you set data.columns=headerName, your log_df['Product']is a single column and you can use strattribute.
设置时data.columns=headerName，您log_df['Product']是单列，您可以使用str属性。
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, strattribute is available.
无论出于何种原因，如果您需要将数据保留为 MultiIndex 对象，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")]
However, I guess the first solution is what you're looking for
但是，我想第一个解决方案是您正在寻找的
