## Python Pandas Series

**A Series **is a one-dimensional labeled array. It can hold any type of data like Integer, Float, String, Python objects, etc. The label is called the index.

### How to create a Series

A series can be created using various inputs like-

- Array
- Dictionary
- constant

#### Create a Series from an array

If data is an array, then the index must be of the same length. If no index is passed, then by default index will be **range(n)** where n is the array length.

Example : 1.

#imports the pandas library and aliasing as pd

import pandas as pd

import numpy as np

data = np.array([‘a’,’b’,’c’,’d’,’e’])

sr=pd.Series(data)

print (sr)

Its output is as follows-

0 | a |

1 | b |

2 | c |

3 | d |

4 | e |

We did not pass any index. By default it assigned the index values ranging from 0 to 4, which is **length(data) **-1, i.e. 0 to 4.

Example : 2.

**#imports the pandas library and aliasing as pd**

**import pandas as pd**

**import numpy as np**

**data = np.array([‘a’,’b’,’c’,’d’,’e’])**

**sr=pd.Series(data, index=[101,102,103,104,105])**

**print (sr)**

Its output is as follows-

101 | a |

102 | b |

103 | c |

104 | d |

105 | e |

#### Create a Series from a dictionary

A dictionary can be passed as input and if no index is specified, then the dictionary keys are taken in a sorted order to construct the index.

Example :

**#imports the pandas library and aliasing as pd**

**import pandas as pd**

**data = {‘a’ : 0, ‘b’ : 1, ‘c’ : 2, ‘d’ : 3}**

**sr=pd.Series(data)**

**print (sr)**

Its output is as follows-

a | 0 |

b | 1 |

c | 2 |

d | 3 |

#### Create a Series from constant

An index must be provided if the data is a scalar value or constant. The value will be repeated to match the length of the index.

Example :

**#imports the pandas library and aliasing as pd**

**import pandas as pd**

**import numpy as np**

**sr=pd.Series(4, index=[0,1,2,3])**

**print (sr)**

Its output is as follows-

0 | 4 |

1 | 4 |

2 | 4 |

3 | 4 |