Python Pandas Series

Pandas Series

Pandas Series is a one-dimensional labeled, homogeneously-typed array.

You can create a series with objects of any datatype. Be it integers, floats, strings, any datatype. You can have a mix of these datatypes in a single series.

In this tutorial, we will learn about Pandas Series with examples.

1. Create Pandas Series

To create Pandas Series in Python, pass a list of values to the Series() class. Pandas will create a default integer index.

In the following example, we will create a pandas Series with integers.

import numpy as np
import pandas as pd

s = pd.Series([1, 3, 5, 12, 6, 8])

print(s)

Output

0     1
1     3
2     5
3    12
4     6
5     8
dtype: int64

The datatype of the elements in the Series is int64. Based on the values present in the series, the datatype of the series is decided.

2. Pandas Series with NaN values

You can also include numpy NaN values in pandas series.

In the following Pandas Series example, we will create a Series with one of the value as numpy.NaN.

import numpy as np
import pandas as pd

s = pd.Series([1, 3, np.nan, 12, 6, 8])

print(s)

Output

0     1.0
1     3.0
2     NaN
3    12.0
4     6.0
5     8.0
dtype: float64

3. Pandas Series with Strings

You can include strings as well for elements in the series.

In the following example, we will create a Pandas Series with one of the value as string.

import numpy as np
import pandas as pd

s = pd.Series(['python', 3, np.nan, 12, 6, 8])

print(s)

Output

0    python
1         3
2       NaN
3        12
4         6
5         8
dtype: object

As the elements belong to different datatypes, like integer and string, the datatype of all the elements in this pandas series is considered as object. But when you access the elements individually, the corresponding datatype is returned, like int64, str, float, etc.

4. Access Elements of Pandas Series

You can access elements of a Pandas Series using index.

In the following Pandas Series example, we create a series and access the elements using index.

import numpy as np
import pandas as pd

s = pd.Series(['python', 3, np.nan, 12, 6, 8])

print(s[0])
print(s[4])

Output

python
6

Summary

In this tutorial of Python Examples, we learned how to create a Pandas Series with elements belonging to different datatypes, and access the elements of the Series using index, with the help of well detailed examples.