Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
Physics
Chemistry
Biology
Mathematics
English
Economics
Psychology
Social Studies
Fashion Studies
Legal Studies
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
How to check the data type of a pandas series?
To check the data type of a Series we have a dedicated attribute in the pandas series properties. The “dtype” is a pandas attribute that is used to verify data type in a pandas Series object.
This attribute will return a dtype object which represents the data type of the given series.
Example 1
# importing required packages
import pandas as pd
import numpy as np
# creating pandas Series object
series = pd.Series(np.random.rand(10))
print(series)
print("Data type: ",series.dtype )Explanation
In this example, we have initialized a pandas series object using NumPy random module, which will create a series with random values.
Let’s apply the pandas dtype property and verify the data type of the series.
Output
0 0.017282 1 0.869889 2 0.255800 3 0.191797 4 0.188235 5 0.261895 6 0.016623 7 0.399498 8 0.642102 9 0.671073 dtype: float64 Data type: float64
In this output block, we can see the series with random values, and the output of the dtype attribute. For the given series object float64 is the data type.
Example 2
import pandas as pd
s = pd.Series({97:'a', 98:'b', 99:'c', 100:'d', 101:'e', 102:'f'})
print(s)
print("Data type: ",s.dtype )Explanation
Create another pandas series object with string data, here we have initialized the series using a python dictionary. Here the goal is to check the data type of the series, so the dtype attribute is applied to the series object “s”.
Output
97 a 98 b 99 c 100 d 101 e 102 f dtype: object Data type: object
For the given series “s” the dtype is an object data type, in general pandas used to represents string data in the form of object data type.
Example 3
import pandas as pd
# creating range sequence of dates
dates = pd.date_range('2021-06-01', periods=5, freq='D')
#creating pandas Series with date index
s = pd.Series(dates)
print (s)
print("Data type: ",s.dtype )Explanation
In this following example, the series is created by using the pandas date_range method and apply the dtype attribute to verify the data type.
Output
0 2021-06-01 1 2021-06-02 2 2021-06-03 3 2021-06-04 4 2021-06-05 dtype: datetime64[ns] Data type: datetime64[ns]
The data type of the given series is datetime64[ns].
12K+ Views
