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# What is the numpy.intersect1d() function in Python?

## What is the numpy.intersect1d() function in Python? Answer

### Overview

NumPy is a popular library for working with arrays. NumPy’s `intersect1d()` function returns the intersection between two arrays. In other words, it returns the common elements for two given arrays.

### Syntax

numpy.intersect1d(ar1, ar2, assume_unique=False, return_indices=False)

### Parameters

This function accepts the following parameter values:

• `ar1` and `ar2`: These two required parameters represent the input arrays for which `intersect1d()` will return the intersection.

Note: `intersect1d()` accepts any array-like objects; this includes NumPy arrays and `scalars`.

Note: If any input array is not one-dimensional, the function will flatten them and convert them to a single dimensional array.

• `assume_unique`: An optional parameter, passed as `True` if both input arrays are assumed to be unique and `False` otherwise. If both input arrays are unique, passing `assume_unique` as `True` can speed up calculation.

Note: If the input arrays are not unique and the user passes `assume_unique` as `True`, the function could return an incorrect result or an out-of-bound exception.

• `return_indices`: An optional parameter, which determines if `intersect1d()` will return two extra arrays containing indices of the elements of the intersection array in the two input arrays.

### Return value

• The function always returns an array that includes the intersection elements found in both the input arrays; this is the intersection array from earlier.
• The function optionally returns two additional arrays, which contain the indices of intersection elements in the input arrays. Each of these two optionally returned arrays represents one input array.

Note: The optional arrays are only returned when the `return_indices` input argument has been set to `True`.

### Example

``````import numpy as np
# creating the input arrays
a = np.array([1,3,5,7,9])
b = np.array([2,4,6,8])

# finding the intersect of the two arrays
print(np.intersect1d(a, b))

# creating the input arrays
c = np.array([[1,2,3], [4,5,6]])
d = np.array([[1,2,3], [4,5,6]])

# finding the intersect of the two arrays
print(np.intersect1d(c, d))

# creating the input arrays
e = np.array([[1,2,3], [7,8,9]])
f = np.array([[1,2,3], [4,5,6]])

# finding the intersect of the two arrays
print(np.intersect1d(e, f, return_indices = True))``````

Hit run to see the results! Try changing input arguments and observe the results.

#### Explanation

• Line 1: We import `numpy` as `np`.
• Lines 3–4: We create two input arrays, `a` and `b`.
• Line 7: We use `intersect1d()` to find the intersection of `a` and `b`, and print the results.
• Lines 10–11: We create two input arrays, `c` and `d`. These are two 2D arrays.
• Line 14: We use `intersect1d()` to find the intersection of `c` and `d` and print the results. The `intersect1d()` function returns a 1D array even though we input two 2D arrays.
• Lines 17–18: We create two input arrays, `e` and `f`.
• Line 21: We use `intersect1d()` to find the intersection of `e` and `f`, and print the results. The `return_indices` argument in `intersect1d()` has been set to `True`. As a result, `intersect1d()` returns two extra arrays, which contain indices of the intersection elements in the two input arrays. `e` and `f` both contain the intersection elements `1``2`, and `3` at indices `0``1`, and `2`.
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