Python | Pandas Series.dtype
Last Updated :
28 Jan, 2019
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.
import pandas as pd
sr = pd.Series([ 'New York' , 'Chicago' , 'Toronto' , 'Lisbon' ])
sr.index = [ 'City 1' , 'City 2' , 'City 3' , 'City 4' ]
print (sr)
|
Output :
Now we will use Series.dtype
attribute to find the data type of the given Series object.
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.
import pandas as pd
sr = pd.Series([ 1000 , 5000 , 1500 , 8222 ])
print (sr)
|
Output :
Now we will use Series.dtype
attribute to find the data type of the given Series object.
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.
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