Pandas - 用名称ID替换数字字符串

Question

I have a column in my dataframe of all Strings some of them are TAG(machines/computers), some other items, and the others are ID's. I am looking to change all the strings that are ID's to "ID" instead of the number-string.

type(df.columnOne[1])
str 

This is what my df column looks like:

df
  columnOne
0 TAG
1 1115268
2 13452
3 system
4 TAG
5 355511
6 95221543
7 5124
8 111333544
9 TAG
10 local
11 434312

Desired output:

df
  columnOne
0 TAG
1 ID
2 ID
3 system
4 TAG
5 ID
6 ID
7 ID
8 ID
9 TAG
10 Local
11 ID

I would normally do something where if it doesn't equal TAG or system or Local then ID. But it is always changing with names.

Answer 1

If I understand correctly, you can use str.isnumeric :

df.loc[df.columnOne.str.isnumeric(),'columnOne'] = 'ID'

>>> df
   columnOne
0        TAG
1         ID
2         ID
3     system
4        TAG
5         ID
6         ID
7         ID
8         ID
9        TAG
10     local
11        ID

Answer 2

Try replace

df.columnOne = df.columnOne.str.replace('\d+', 'ID')

0        TAG
1         ID
2         ID
3     system
4        TAG
5         ID
6         ID
7         ID
8         ID
9        TAG
10     local
11        ID

Answer 3

As RafaelC mentioned in the comment , if contain float

df.loc[pd.to_numeric(df.columnOne,errors='coerce').notna(),'columnOne']='ID'
df
Out[536]: 
   columnOne
0        TAG
1         ID
2         ID
3     system
4        TAG
5         ID
6         ID
7         ID
8         ID
9        TAG
10     local
11        ID

Answer 4

Solution using apply:
(just for completeness, str.replace and str.isnumeric solutions are much more simple)

df = pd.DataFrame({'columnOne': ['TAG', 
                                 '1111', 
                                 'system']})

def ids_replace(x):
    try:
        int(x)
        return 'ID'
    except ValueError:
        return x

print(df.apply(ids_replace, axis=1))

> columnOne
0   TAG
1   ID
2   system