In this tutorial, we will know how to get the data type of a column in a Pandas Dataframe.
Later, we will understand the same with the help of a few examples.
How to get column dtype in a Pandas Dataframe?
You can get the dtype of a pandas datafrmae column using the column dtype
attribute and the dtypes of all the columns with the dataframe .dtypes
attribute.
1. .dtype
attribute :
You can get the column data type of a particular column, using the .dtype
attribute along with the dataframe name and column name specified.
Syntax: dataFrameName['ColumnName'].dtype
2. .dtypes
attribute:
In case you want to know the data types of all columns in the dataframe, you can use the .dtypes attribute along with the dataframe name.
Syntax: dataFrameName.dtypes
Introductory ⭐
- Harvard University Data Science: Learn R Basics for Data Science
- Standford University Data Science: Introduction to Machine Learning
- UC Davis Data Science: Learn SQL Basics for Data Science
- IBM Data Science: Professional Certificate in Data Science
- IBM Data Analysis: Professional Certificate in Data Analytics
- Google Data Analysis: Professional Certificate in Data Analytics
- IBM Data Science: Professional Certificate in Python Data Science
- IBM Data Engineering Fundamentals: Python Basics for Data Science
Intermediate ⭐⭐⭐
- Harvard University Learning Python for Data Science: Introduction to Data Science with Python
- Harvard University Computer Science Courses: Using Python for Research
- IBM Python Data Science: Visualizing Data with Python
- DeepLearning.AI Data Science and Machine Learning: Deep Learning Specialization
Advanced ⭐⭐⭐⭐⭐
- UC San Diego Data Science: Python for Data Science
- UC San Diego Data Science: Probability and Statistics in Data Science using Python
- Google Data Analysis: Professional Certificate in Advanced Data Analytics
- MIT Statistics and Data Science: Machine Learning with Python - from Linear Models to Deep Learning
- MIT Statistics and Data Science: MicroMasters® Program in Statistics and Data Science
🔎 Find Data Science Programs 👨💻 111,889 already enrolled
Disclaimer: Data Science Parichay is reader supported. When you purchase a course through a link on this site, we may earn a small commission at no additional cost to you. Earned commissions help support this website and its team of writers.
Examples
We will now look at a few examples for a better understanding.
But before that, we will create a pandas dataframe that we will be using throughout this tutorial using the following command:
import pandas as pd # employee data data = { "Name": ["Jim", "Dwight", "Angela", "Tobi"], "Age": [26, 28, 27, 32], "Department": ["Sales", "Sales", "Accounting", "HR"] } # create pandas dataframe df = pd.DataFrame(data) # displays dataframe df
Output:

Example 1: Get the data type of a specific column in dataframe

Let’s get the dtype of the “Age” column from the above dataframe.
# dtype of the "Age" column df['Age'].dtype
Output:
dtype('int64')
Example 2: Get the data type of all columns in the dataframe
Let’s now get the dtypes of all the columns present in the dataframe above.
# dtypes of all the columns in the dataframe df.dtypes
Output:
Name object Age int64 Department object dtype: object
Summary
In this tutorial, we looked at how to get column data type(s) in a Pandas dataframe. Following are the key takeaways –
- Use the
.dtype
attribute to get the data type of a particular column in a Pandas dataframe. First, select the column and then use this attribute to get its dtype. - Use the dataframe
.dtypes
attribute to get the data type of all columns in a Pandas dataframe.
You might also be interested in –
- Check if Pandas DataFrame column has object dtype
- Check if Pandas DataFrame column has object dtype
- Check if Pandas DataFrame column has object dtype
- Get Count of dtypes in a Pandas DataFrame
Subscribe to our newsletter for more informative guides and tutorials.
We do not spam and you can opt out any time.