Python | Pandas Series.dtype



Python | Pandas Series.dtype

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.

Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index.

Pandas Series.dtype attribute returns the data type of the underlying data for the given Series object.

Syntax: Series.dtype

Parameter : None

Returns : data type

Example #1: Use Series.dtype attribute to find the data type of the underlying data for the given Series object.

# importing pandas as pd
import pandas as pd
 
# Creating the Series
sr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon'])
 
# Creating the row axis labels
sr.index = ['City 1', 'City 2', 'City 3', 'City 4'
 
# Print the series
print(sr)

Output :

Now we will use Series.dtype attribute to find the data type of the given Series object.

# return the data type
sr.dtype

Output :

As we can see in the output, the Series.dtype attribute has returned ‘O’ indicating the data type of the underlying data is object type.

 

Example #2 : Use Series.dtype attribute to find the data type of the underlying data for the given Series object.

# importing pandas as pd
import pandas as pd
 
# Creating the Series
sr = pd.Series([1000, 5000, 1500, 8222])
 
# Print the series
print(sr)

Output :

Now we will use Series.dtype attribute to find the data type of the given Series object.

# return the data type
sr.dtype

Output :

As we can see in the output, the Series.dtype attribute has returned ‘int64’ indicating the data type of the underlying data is of int64 type.

 

Last Updated on October 19, 2021 by admin

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