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# Python for Basic Data Analysis: NP.13 Analysing data across arrays

Get started on your learning journey towards data science using Python. Equip yourself with practical skills in Python programming for the purpose of basic data manipulation and analysis.

## Comparing 2 arrays

##### Comparing 2 arrays

You can select elements in an array based on conditions. Let's begin with 2 arrays.

## Analysing data across arrays

##### np.where

`np.where` lets you select elements from an array based on conditions. It returns the index of the elements that meets the conditions.

In this example, using the 2 arrays from above, we can use `np.where` to find which:

1. elements that are the same in both arrays
2. elements in `x` that are bigger than or equal to its corresponding element in `y`
3. elements in `x` multiplied by 2 that are smaller than its corresponding element in `y`
4. elements in `y` that are bigger than 5

##### Boolean indexing

Conditional operators like `=``<`, `>` can be used to compare arrays. Using them will return Boolean values.

In addition, you can use this syntax to return the index of elements that meets the condition:

`y [y > 3]`

Similarly, you can also use `np.where`:

## Exercises

Use these arrays for the following practice:

```myArray_1 = np.array([2,2,3,4])
myArray_2 = np.array([3,2,3,4])```

1. Find the elements that are the same in both arrays

2. Find elements in `myArray_1` that are smaller than or equal to its corresponding element in `myArray_2`

3. Find the elements in `myArray_1` that is bigger than 2

1. Find the elements that are the same in both arrays

2. Find elements in `myArray_1` that are smaller than or equal to its corresponding element in `myArray_2`

3. Find the elements in `myArray_1` that is bigger than 2