How to (idiomatically) use pandas .loc to return an empty dataframe when key is not in index [duplicate] - pandas

Question

This question already has answers here:
Pandas .loc without KeyError
(6 answers)
Closed 2 years ago.
Say I have a DataFrame (with a multi-index, for that matter), and I wish to take the values at some index - but, if that index does not exist, I wish for it to return an empty df instead of a KeyError.
I've searched for similar questions, but they are all about pandas returning an empty dataframe when it is not desired at some cases (conversely, I do desire an empty dataframe in return).
For example:
import pandas as pd
df = pd.DataFrame(index=pd.MultiIndex.from_tuples([(1,1),(1,2),(3,1)]),
columns=['a','b'], data=[[1,2],[3,4],[10,20]])
so, df is:
a b
1 1 1 2
2 3 4
3 1 10 20
and df.loc[1] is:
a b
1 1 2
2 3 4
df.loc[2] raises a KeyError, and I'd like something that returns
a b
The closest I could get is by calling df.loc[idx:idx] as a slice, which gives the correct result for idx=2, but for idx=1 it returns
a b
1 1 1 2
2 3 4
instead of the desires result.
Of course I can define a function to do it,

Answer 1

One idea with if-else statament:
def get_val(x):
return df.loc[x] if x in df.index.levels[0] else pd.DataFrame(columns=df.columns)
Or generally with try-except statement:
def get_val(x):
try:
return df.loc[x]
except KeyError:
return pd.DataFrame(columns=df.columns)
print (get_val(1))
a b
1 1 2
2 3 4
print (get_val(2))
Empty DataFrame
Columns: [a, b]
Index: []