How to remove rows from a dataframe based on a particular text

Question

My Data frame has several columns,

Id	Name	age
1	John Camp	25
2	Richard	35
3	John Randell	29
4	John Cameron	26
5	John Jacob	28
6	Oliver	24
7	Eugene	22
8	John Camp	21
9	John Clark	29
10	John Rick	21

Intended Output:

Id	Name	age
1	John Camp	25
2	Richard	35
4	John Cameron	26
6	Oliver	24
7	Eugene	27
8	John Camp	25
10	John Rick	21

I need to delete those names starting with John who are not (Camp,Cameron,Rick) while keeping the rest of the names.

1. John Camp
2. John Cameron
3. John Rick

I want to remove only those Johns who aren't in the given three names above, while keeping other names.

Can someone help me with this?

Answer 1

Use Series.str.endswith wit htuple of surname chained by | for bitwise OR with Series.str.startswith and inverted mask by ~ and filter in boolean indexing:

sur = ['Camp', 'Cameron', 'Rick']

df = df[df['Name'].str.endswith(tuple(sur)) | ~df['Name'].str.startswith('John')]
print (df)
   Id          Name  age
0   1     John Camp   25
1   2       Richard   35
3   4  John Cameron   26
5   6        Oliver   24
6   7        Eugene   22
7   8     John Camp   21
9  10     John Rick   21