Python Data Types: Sets - Exercises, Practice, Solution
Python Sets [ 20 exercises with solution]
A set object is an unordered collection of distinct hashable objects. It is commonly used in membership testing, removing duplicates from a sequence, and computing mathematical operations such as intersection, union, difference, and symmetric difference.
You may read our Python sets tutorial before solving the following exercises.
[An editor is available at the bottom of the page to write and execute the scripts.]
1. Write a Python program to create a set. Go to the editor
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2. Write a Python program to iteration over sets. Go to the editor
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3. Write a Python program to add member(s) in a set. Go to the editor
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4. Write a Python program to remove item(s) from a given set. Go to the editor
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5. Write a Python program to remove an item from a set if it is present in the set. Go to the editor
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6. Write a Python program to create an intersection of sets. Go to the editor
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7. Write a Python program to create a union of sets. Go to the editor
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8. Write a Python program to create set difference. Go to the editor
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9. Write a Python program to create a symmetric difference. Go to the editor
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10. Write a Python program to check if a set is a subset of another set. Go to the editor
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11. Write a Python program to create a shallow copy of sets. Go to the editor
Note : Shallow copy is a bit-wise copy of an object. A new object is created that has an exact copy of the values in the original object.
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12. Write a Python program to remove all elements from a given set. Go to the editor
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13. Write a Python program to use of frozensets. Go to the editor
Note: Frozensets behave just like sets except they are immutable.
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14. Write a Python program to find maximum and the minimum value in a set. Go to the editor
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15. Write a Python program to find the length of a set. Go to the editor
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16. Write a Python program to check if a given value is present in a set or not. Go to the editor
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17. Write a Python program to check if two given sets have no elements in common. Go to the editor
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18. Write a Python program to check if a given set is superset of itself and superset of another given set. Go to the editor
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19. Write a Python program to find the elements in a given set that are not in another set. Go to the editor
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20. Write a Python program to remove the intersection of a 2nd set from the 1st set. Go to the editor
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Python: Tips of the Day
Understanding slice notation:
It's pretty simple really:
a[start:stop] # items start through stop-1 a[start:] # items start through the rest of the array a[:stop] # items from the beginning through stop-1 a[:] # a copy of the whole array
There is also the step value, which can be used with any of the above:
a[start:stop:step] # start through not past stop, by step
The key point to remember is that the :stop value represents the first value that is not in the selected slice. So, the difference between stop and start is the number of elements selected (if step is 1, the default).
The other feature is that start or stop may be a negative number, which means it counts from the end of the array instead of the beginning. So:
a[-1] # last item in the array a[-2:] # last two items in the array a[:-2] # everything except the last two items
Similarly, step may be a negative number:
a[::-1] # all items in the array, reversed a[1::-1] # the first two items, reversed a[:-3:-1] # the last two items, reversed a[-3::-1] # everything except the last two items, reversed
Python is kind to the programmer if there are fewer items than you ask for. For example, if you ask for a[:-2] and a only contains one element, you get an empty list instead of an error. Sometimes you would prefer the error, so you have to be aware that this may happen.
Relation to slice() object
The slicing operator [] is actually being used in the above code with a slice() object using the : notation (which is only valid within []), i.e.:
a[start:stop:step]
is equivalent to:
a[slice(start, stop, step)]
Slice objects also behave slightly differently depending on the number of arguments, similarly to range(), i.e. both slice(stop) and slice(start, stop[, step]) are supported. To skip specifying a given argument, one might use None, so that e.g. a[start:] is equivalent to a[slice(start, None)] or a[::-1] is equivalent to a[slice(None, None, -1)].
While the : -based notation is very helpful for simple slicing, the explicit use of slice() objects simplifies the programmatic generation of slicing.
Ref: https://bit.ly/2MHaTp7
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