Python input to select specific rows

I have a dataframe where I would like to utilize Input function to select a row or a group of rows.

Data

type    stat    country
aa1     y       ca
bb2     n       ny
cc3     y       tx

Desired

Use Input("select type value:  ")

type in:  aa1, bb2

*selects appropriate rows

type    stat    country 
aa1     y       ca  
bb2     n       ny  

Doing

out = Input("select type value:  ")
df.loc[df['type'].isin([aa1, bb2])]

I am thinking that I can combine .loc along w input() Any suggestion is appreciated.

Because input is strings with , only use split for list ['aa1','bb2'] with strip for remove traliling spaces, because type aa1,bb2 not aa1, bb2 like mentioned in question:

df[df['type'].isin([x.strip() for x in out.split(',')])]

Use query:

out = input("select type value:  ")
vals = [v.strip() for v in out.split(',')]
df1 = df.query('type.isin(@vals)')
print(df1)

Ouput

select type value:  aa1,bb2

  type stat country
0  aa1    y      ca
1  bb2    n      ny

Update

Is there a way to capture the remaining dataset? once selected (The subset that was not sliced)

Use a boolean mask:

out = input("select type value:  ")
vals = [v.strip() for v in out.split(',')]

mask = df['type'].isin(vals)
df1 = df.loc[mask]
df2 = df.loc[~mask]

Output:

>>> df1
  type stat country
0  aa1    y      ca
1  bb2    n      ny

>>> df2
  type stat country
2  cc3    y      tx