Pandas Series a Python’s Library for Data Handling

Pandas Series

Series is like one dimensional array or a column in a table and can be hold any type data. Furthermore, pandas series can be created in two ways.

1- Create a Pandas Series with Default Indices-

In this method, you can create a series by passing list inside Series() method. As a result, the method will create a series having indices 0, 1, 2, 3.

import pandas as pd
l=[1,5,9,13]
ser=pd.Series(l)
print(ser)

Output:

0         1
1        5
2        9
3       13
dtype: int64

2- Create a Pandas Series with Customize Indices-

In this method, you can create a series by passing a list and a list of indices inside Series() method. As a result, the below program will create a series having indices a, b, , c and d.

import pandas as pd
l=[1,5,9,13]
i=["a","b","c", "d"]
ser=pd.Series(l, index=i)
print(ser)

Output:

a         1
b        5
c        9
d       13
dtype: int64

Access Individual Element from a Series

You can also access an element like you access in list see the below example:

import pandas as pd
l=[1,5,9,13]
i=["a","b","c","d"]
ser=pd.Series(l,index=i)
print(ser["c"])

Output: 9

Print Type of Series

import pandas as pd
l=[1,5,9,13]
i=["a","b","c", "d"]
ser=pd.Series(l, index=i)
print(type(ser))
Output:
<class 'pandas.core.series.Series'>

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