In [1]: df = pd.DataFrame({'A': [5,6,3,4], 'B': [1,2,3,5]})
In [2]: df
Out[2]:
A B
0 5 1
1 6 2
2 3 3
3 4 5
In [3]: df[df['A'].isin([3, 6])]
Out[3]:
A B
1 6 2
2 3 3df.iloc[[1, 5]] # Get rows 1 and 5
df.iloc[1:6] # Get rows 1 to 5 inclusive
df.iloc[[1, 5], df.columns.get_loc('Shop')] # Get only specific column
df.iloc[[1, 5], df.columns.get_indexer(['Shop', 'Category'])] # Get multiple columnsif(all(x in test_list for x in sub_list)):
flag = Truenew = old.filter(['A','B','D'], axis=1) smallSet = {'a', 'b'}
superSet = {'a', 'b', 'c'}
print(smallSet.issubset(superSet)) # This will return True
print(superSet.issubset(smallSet)) # This will return False
n,su = map(int,input().split())
A = list(map(int,input().split()[:n]))
s = []
for i in range(0,len(A)+1):
for j in range(i+1,len(A)+1):
s.append(A[i:j])
for k in s:
if sum(k) == su:
f = 1
break
if f == 1:
print("TRUE")
else:
print("FALSE")