**Summary: **in this tutorial, you’ll learn about the two main data structures of Pandas – the Series and DataFrame.

## Pandas Series

**The Series is the most basic data structure of pandas.**

Assuming you’re already familiar with Python data types, the `Series `

looks pretty similar to a list in Python. The core difference between a List and a Series is that the Series allows you to use anything you like as the index, instead of restricting on zero-based array indexes.

A Series object contains two “columns”, the first one is the index, the second one contains our data. By default, the index is number based and starts from zero.

```
import numpy as np
import pandas as pd
# This is a Series
# with number-based indexes
example = pd.Series([1,2,3,4,5])
example
# Output :
0 1
1 2
2 3
3 4
4 5
dtype: int64
```

You can retrieve one or multiple items from a `Series`

using the indexes.

```
# Retrieving a single value #
example[3]
# Output
4
# Retrieving multiple values #
example[[2,4]]
# Output
2 3
4 5
dtype: int64
```

But you can **specify your own index by passing an index argument.**

```
import numpy as np
import pandas as pd
# This is another Series
# with character-based indexes
example = pd.Series([1,2,3,4,5],
index=['a', 'b', 'c', 'd', 'e'])
example
# Output :
a 1
b 2
c 3
d 4
e 5
dtype: int64
```

By specifying a custom index column, you can access items from those indexes.

```
# Retrieving a single value #
example['c']
# Output
3
# Retrieving multiple values #
example[[c,e]]
# Output
c 3
e 5
dtype: int64
```

You can also perform other statistical operations with a Series, a common one is to get the mean of all values in a Series object.

```
# Get the means of the values
example.mean()
# Output
3.0
```

While not being particularly useful than the ordinary list at first, Series is the base of the next powerful data types of Pandas : the DataFrame.

**Summary: **Series is a list with customizable indexes, serve as the base of DataFrame.

**Author: Thijmen**I’m currently a SysAdmin located in the Netherlands. Every day I try to keep around a hundred users happy with their network connections and overall, tech-related issues. I also spend my spare time fiddling with web-based applications.