Why python skips elif statement

What I am trying to do is to let user input a set of values separated with spaces, read them, compare correctly with the dataframe and print text accordingly.
What may look like a simple task turned out in many hours of struggling.
What is strange:

1. else statement by itself is working properly, but its formatting differs from if statement
2. if statement formatting seems correct, but it doesn't work right.
   It always prints that 'All numbers are in dataframe' no matter what I type in.
3. elif statement is never recognized

I converted input str to list, which can be seen in the code example.
So, this is clearly not related to data type.
Any help will be very appreciated!

import pandas as pd

in1 = input("Choose certain numbers separated with spaces:")
in1 = in1.strip()

result = pd.DataFrame([1, 1, 1, 2, 3, 3, 4, 5], columns=['Numbers'])

uniq_numbers = list(result.Numbers.unique())

print(type(in1))
in1 = in1.split()
for i in range(len(in1)):
    in1[i] = int(in1[i])
print(type(in1))

if all(result[(result['Numbers'].isin([in1]))]):
    print('All numbers', in1, ' are in dataframe:', uniq_numbers)
elif not all(result['Numbers'].isin(in1)):
    print('No numbers', in1, ' were found in dataframe!', uniq_numbers)
else:
    print('Some of the numbers entered:', in1, 'are NOT in dataframe, be aware. \n',
     'Valid number/s:',
     set(in1).intersection(result),
     '\n Number/s that were NOT found in dataframe:',
     (set(in1) - set(result))
          )

Input: 6 7
Output:
All numbers are in dataframe
['6', ' ', '7']

Please try the following:
I think it will solve your problem:

import pandas as pd

in1 = input("Choose certain numbers separated with spaces:")
in1 = in1.strip()

result = pd.DataFrame([1, 1, 1, 2, 3, 3, 4, 5], columns=['Numbers'])

uniq_numbers = list(result.Numbers.unique())

print(type(in1))
in1 = in1.split()
for i in range(len(in1)):
    in1[i] = int(in1[i])
print(type(in1))

in1_set = set(in1)
uniq_numbers_set = set(uniq_numbers)

if in1_set.issubset(uniq_numbers_set):
    print('All numbers', in1, ' are in dataframe:', uniq_numbers)
elif not in1_set.intersection(uniq_numbers_set):
    print('No numbers', in1, ' were found in dataframe!', uniq_numbers)
else:
    print('Some of the numbers entered:', in1, 'are NOT in dataframe, be aware. \n',
     'Valid number/s:',
     in1_set.intersection(uniq_numbers_set),
     '\n Number/s that were NOT found in dataframe:',
     in1_set - uniq_numbers_set
          )

In this corrected code, we convert in1 and uniq_numbers to sets and use the issubset method to check if all numbers in in1 are in the DataFrame. We also use the intersection method to check if any numbers in in1 are in the DataFrame.

There are two major problems. You are not testing whether all numbers in the list are in the data frame, but rather if all numbers in the data frame are in the list. The problem with the if statement is that as the argument of the all function you are not using an iterable of bools, but rather an object, data frame in this case.

To test whether all numbers in the list are in the data frame you can use numpy:

import numpy as np
import pandas as pd

result = pd.DataFrame([1, 1, 1, 2, 3, 3, 4, 5], columns=['Numbers'])
numbers = [1, 3, 5]
mask = np.isin(numbers, result['Numbers'].unique())

if np.all(mask):
    print('All numbers present')
elif not np.any(mask):
    print('None numbers present')
else:
    print('Some numbers present')

To know which numbers from the list are present in the data frame, you can use the mask variable. Number numbers[i] is present in the data frame if mask[i] is True. If you transform numbers to numpy array, you can simply get all present numbers as

numbers_present = np.array(numbers)[mask]

This is possible, because you can index numpy arrays using bools.