Pandas - Series Attributes

Series attributes reflect information that is intrinsic to the series. Accessing a series through its attributes allows us to get the intrinsic properties of the series. Most commonly used attributes are mentioned below:

Lets discuss these attributes in detail:

Series.dtype

The dtype attribute is used to get the dtype object of the given series. Consider the following example.

import pandas as pd

x = pd.Series([10, 20, 30])
y = pd.Series(["abc", "xyz"])

print("dtype of x:", x.dtype)
print("dtype of y:", y.dtype)

The output of the above code will be:

dtype of x: int64
dtype of y: object

Series.empty

The empty attribute is used to check whether the given Series is empty or not.

import pandas as pd
Name = ['John', 'Marry', 'Jo', 'Sam']
x = pd.Series(Name)
y = pd.Series(dtype="float64")

print("Is x empty?:", x.empty)
print("Is y empty?:", y.empty)

The output of the above code will be:

Is x empty?: False
Is y empty?: True

Series.index

The index attribute is used to return the index (axis labels) of the Series.

import pandas as pd
Name = ['John', 'Marry', 'Jo', 'Sam']
x = pd.Series(Name)

print("The Series contains:")
print(x)

print("\nThe index (axis labels) are:")
print(x.index)

The output of the above code will be:

The Series contains:
0     John
1    Marry
2       Jo
3      Sam
dtype: object

The index (axis labels) are:
RangeIndex(start=0, stop=4, step=1)

The above result is written in a compact format which can be interpreted as [0, 1, 2, 3].

Series.ndim

The ndim attribute is used to get the dimensions of the given Series, which is by definition should be 1.

import pandas as pd
Colors = ['Red', 'Blue', 'Green', 'White']
x = pd.Series(Colors)

#dimension of x
print("Dimension of x:", x.ndim)

The output of the above code will be:

Dimension of x: 1

Series.shape

The shape attribute can be used to get a tuple of the shape of the underlying data. Consider the following example.

import pandas as pd
Numbers = [60, 55, 62, 58, 78]
y = pd.Series(Numbers)

#shape of y
print("Shape of y:", y.shape)

The output of the above code will be:

Shape of y: (5,)

Series.size

The size attribute is used to get number of elements in the given Series. Consider the example below:

import pandas as pd
Name = ['John', 'Marry', 'Jo', 'Sam']
x = pd.Series(Name)

print("The Series is:")
print(x)

print("\nThe number of elements in the Series:", x.size)

The output of the above code will be:

The Series is:
0     John
1    Marry
2       Jo
3      Sam
dtype: object

The number of elements in the Series: 4

Series.values

The values attribute is used to return the actual data in the series as an array. Consider the following example:

import pandas as pd
Name = ['John', 'Marry', 'Jo', 'Sam']
x = pd.Series(Name)

print("The Series is:")
print(x)

print("\nThe actual data in the series is:")
print(x.values)

The output of the above code will be:

The Series is:
0     John
1    Marry
2       Jo
3      Sam
dtype: object

The actual data in the series is:
['John' 'Marry' 'Jo' 'Sam']