遍历熊猫数据框并应用条件

Question

考虑一下我有这个数据框，我想从主题列中删除玩具作为主题，如果有一个主题作为玩具的行，则删除该行。我们如何在熊猫中做到这一点？

+---+-----------------------------------+-------------------------+
|   |           Comment                 |            Topic        |
+---+-----------------------------------+-------------------------+
| 1 |             -----                 | toy, bottle, vegetable  | 
| 2 |             -----                 | fruit, toy, electronics |  
| 3 |             -----                 | toy                     |  
| 4 |             -----                 | electronics, fruit      |  
| 5 |             -----                 | toy, electronic         |           
+---+-----------------------------------+-------------------------+

Answer 1

尝试在str.replace内使用str.rstrip和ne的{​​{1}}：

[...]

Answer 2

在这种情况下

lambda函数可以派上用场

df['topic'] = df['topic'].apply(lambda x: "" if len(x.split(','))==1 and x.split(',')[0]=='toy'))

Answer 3

# create data dummy test data
data = {'comment':[1,2,3,4,5],
        'Topic':['toy, bottle, vegetable','fruit, toy, electronics','toy','electronics, fruit','toy, electronic']}

# create dataframe
df = pd.DataFrame(data)

# create function to tidy your data and remove toy
def remove_toy(row):
    row = [i.strip() for i in row.split(',')]
    row = [i for i in row if i != 'toy']
    return ', '.join(row)

# apply function to series
df['Topic'] = df['Topic'].apply(remove_toy)

#remove empy rows in the Topic series
df = df[df['Topic']!='']