Pandas series is a one-dimensional data structure. It can hold data of many types including objects, floats, strings and integers. You can create a series by calling `pandas.Series()`

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An list, numpy array, dict can be turned into a pandas series. You should use the simplest data structure that meets your needs. In this article we’ll discuss the series data structure.

**Related course:** Data Analysis with Python Pandas

## Create series

### Introduction

Pandas comes with many data structures for processing data. One of them is a series.

The syntax for a series is:

1 | import pandas as pd |

This creates an empty series.

### Create series from list

To turn a list into a series, all you have to do is:

1 | import pandas as pd |

The contents of s is:

0 1

1 2

2 3

3 4

dtype: int64

By default is assigns an index. First it shows the index, then the element value.

### Create series from ndarray

You can create a series from a numpy ndarray.

1 | import pandas as pd |

This ouputs the following:

1 | >>> s |

### Create a series from a dict

If you have a dictionary, you can turn it into a series:

1 | import pandas as pd |

The contents of the series is as follows:

1 | s |

As index it used the dictionary keys.

## Pandas series

### Pandas series get index

You can access series data like you would with a list or ndarray.

1 | import pandas as pd |

You slice a series, like you would with a list:

1 | 1,2,3,4,5,6]) data = np.array([ |

1 | 3:5] s[ |

**Related course:** Data Analysis with Python Pandas