# Python for Basic Data Analysis

Start your data science journey with Python. Learn practical Python programming skills for 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