如何从Pandas数据框中的列表中删除值? [英] How to remove a value from a list in a Pandas dataframe?

问题描述

我创建了一个数据框:

[in] testing_df =pd.DataFrame(test_array,columns=['transaction_id','product_id'])

# Split the product_id's for the testing data
testing_df.set_index(['transaction_id'],inplace=True)
testing_df['product_id'] = testing_df['product_id'].apply(lambda row: row.split(','))

[out]                 product_id
transaction_id                 
001                       [P01]
002                  [P01, P02]
003             [P01, P02, P09]
004                  [P01, P03]
005             [P01, P03, P05]
006             [P01, P03, P07]
007             [P01, P03, P08]
008                  [P01, P04]
009             [P01, P04, P05]
010             [P01, P04, P08]

现在如何从结果中删除"P04"和"P08"?

How can I now remove 'P04' and 'P08' from the results?

我尝试过:

# Remove P04 and P08 from consideration
testing_df['product_id'] = testing_df['product_id'].map(lambda x: x.strip('P04'))

testing_df['product_id'].replace(regex=True,inplace=True,to_replace=r'P04,',value=r'')

但是，这两个选项似乎都不起作用.

However, neither option seems to work.

数据类型为:

[in] print(testing_df.dtypes)
[out] product_id    object
dtype: object

[in] print(testing_df['product_id'].dtypes)
[out] object

推荐答案

将要删除的所有元素存储在列表中.

store all your elements to be removed in a list.

remove_results = ['P04','P08']
for k in range(len(testing_df['product_id'])):
    for r in remove_results:
        if r in testing_df['product_id'][k]:
            testing_df['product_id][k].remove(r)

这篇关于如何从Pandas数据框中的列表中删除值?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！