Coding Ref

The `map()`

function is a built-in Python function that allows you to apply a function to every element of an iterable, such as a list or a Pandas Series.

We will learn about the `map()`

function and how to use it in Pandas to transform data.

To illustrate, let's create a simple Pandas Series with some random data:

main.py

```
import pandas as pd
# create a Series with some random data
s = pd.Series([1, 2, 3, 4, 5])
# print the Series
print(s)
```

The resulting Series will look like this:

output

```
0 1
1 2
2 3
3 4
4 5
dtype: int64
```

Now, let's use the `map()`

function to apply a function to every element of the Series. For example, let's say we want to square each element in the Series. To do this, we can use the `map()`

function and pass it the `pow()`

function with the second argument set to 2:

main.py

```
# square each element in the Series
squared = s.map(pow, 2)
# print the result
print(squared)
```

This will output the squared values of each element in the Series:

output

```
0 1
1 4
2 9
3 16
4 25
dtype: int64
```

In this case, the `map()`

function applies the `pow()`

function to each element of the Series, which squares each element and returns a new Series with the squared values.

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