## Introducing pandas series

Level: Beginner (score: 2)

Let's get started with Pandas! In case you are not aware of who, or what, `pandas`

is, pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.

The two primary data structures in `pandas`

are the ** Series** and the

**. The simplest way to visualise these two structures is to use an analogy with your favourite Spreadsheet application. Think of a**

*DataFrame*`pandas`

Series as Column A of Sheet 1 of your spreadsheet. Looking at the screen grab below it has 1 dimension (Column A) that represents the Series values, plus the row numbers which represent the indexes. A Dataframe is the whole spreadsheet, 2 dimensions or multiple columns, but more of that later.This is what a Series looks like in a Spreadsheet.

In a spreadsheet the row indexes typically start at `1`

and the column names typically start at `A`

. The Series called `A`

above has four value `[1, 2, 3, 4]`

.

This is what a similar Series looks like in `pandas`

:

>>> x 0 1 1 2 2 3 Name: Fred, dtype: int64

The `pandas`

Series Python variable is named `x`

. The default index, like all other Python objects, are zero-based so the index values are `[0, 1, 2]`

and the series values are `[1, 2, 3]`

. The sample `x`

series shown is called `Fred`

and all the series values are of type `int64`

.

#### Creating Series

Now that you know everything that you need to know about `pandas`

Series it's time for you to start creating some series of your own. In this Bite you are asked to complete a number of functions that each create a `pandas`

Series. How you create each series is up to you but if you do your research you'll find that Series can be created from all different type of Python Objects:

- Create a Series with values
`[1, 2, 3, 4, 5]`

of type`int64`

, don't worry about the index but make`Fred`

the name of the Series - Create a Series with values
`[0.000, 0.001, ... 0.999, 1.000]`

of type`float64`

, don't worry about the index - Create a Series with values
`[1, 2, ... 25, 26]`

of type`int64`

, and add an index with values`[a, b, ... y, z]`

so index`a = 1`

,`b = 2`

...`y = 25`

,`z = 26`

- Create a Series with values
`[A, B, ... Y, Z]`

of type`object`

, and add an index with values`[101, 102, ... 125, 126]`

so index`101 = 'A'`

,`102 = 'B'`

...`125 = 'Y'`

,`126 = 'Z'`

In the the next Bite we'll look at getting the values out of the Series in a useful manner.