如何在Pandas Python中使用另一个数据框替换数据框中的单词

Question

我有两个数据框：

df：

id   string_data
1    My name is Jeff
2    Hello, I am John
3    I like Brad he is cool.

另一个名为的数据框allnames包含这样的名称列表：

id  name
1   Jeff
2   Brad
3   John
4   Emily
5   Ross

我想将df其中出现的所有单词替换allnames['name']为"Firstname"

预期产量：

id   string_data
1    My name is Firstname
2    Hello, I am Firstname
3    I like Firstname he is cool.

我尝试了这个：

nameList = '|'.join(allnames['name'])
df['string_data'].str.replace(nameList, "FirstName", case = False))

但它取代了几乎99％的单词

Answer 1

Your solution should working if add words boundaries to Series.str.replace:

nameList = '|'.join(r"\b{}\b".format(x) for x in allnames['name'])
df['string_data'] = df['string_data'].str.replace(nameList, "FirstName", case = False)
print (df)
   id                   string_data
0   1          My name is FirstName
1   2         Hello, I am FirstName
2   3  I like FirstName he is cool.

Or replace values with get and join by dictionary:

d = dict.fromkeys(allnames['name'], 'Firstname')
f = lambda x: ' '.join(d.get(y, y) for y in x.split())
df['string_data'] = df['string_data'].apply(f)
print (df)
   id                   string_data
0   1          My name is Firstname
1   2         Hello, I am Firstname
2   3  I like Firstname he is cool.

EDIT: You can convert all values to lowercase by lower:

d = dict.fromkeys([x.lower() for x in allnames['name']], 'Firstname')
f = lambda x: ' '.join(d.get(y.lower(), y) for y in x.split())
df['string_data'] = df['string_data'].apply(f)