Pandas DataFrame is a two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). Arithmetic operations align on both row and column labels. It can be thought of as a dict-like container for Series objects. This is the primary data structure of the Pandas. Pandas DataFrame.dtypes attribute return the dtypes in the DataFrame. It returns a Series with the data type of each column.
Pandas DataFrame.dtypes Syntax
Syntax: DataFrame.dtypes
Parameter : None
Returns : dtype of each column
Example 1: Use DataFrame.dtypes attribute to find out the data type (dtype) of each column in the given Dataframe.
Python3
# importing pandas as pdimport pandas as pd # Creating the DataFramedf = pd.DataFrame({'Weight': [45, 88, 56, 15, 71], 'Name': ['Sam', 'Andrea', 'Alex', 'Robin', 'Kia'], 'Age': [14, 25, 55, 8, 21]}) # Create the indexindex_ = ['Row_1', 'Row_2', 'Row_3', 'Row_4', 'Row_5'] # Set the indexdf.index = index_ # Print the DataFrameprint(df) |
Output :
Now we will use DataFrame.dtypes attribute to find out the data type of each column in the given Dataframe.
Python3
# return the dtype of each columnresult = df.dtypes # Print the resultprint(result) |
Output:
As we can see in the output, the DataFrame.dtypes attribute has successfully returned the data types of each column in the given Dataframe.
Example 2: Use DataFrame.dtypes attribute to find out the data type (dtype) of each column in the given dataframe.
Python3
# importing pandas as pdimport pandas as pd # Creating the DataFramedf = pd.DataFrame({& quot A": [12, 4, 5, None, 1], & quot B" : [7, 2, 54, 3, None], & quot C" : [20, 16, 11, 3, 8], & quot D" : [14, 3, None, 2, 6]}) # Create the indexindex_ = ['Row_1', 'Row_2', 'Row_3', 'Row_4', 'Row_5'] # Set the indexdf.index = index_ # Print the DataFrameprint(df) |
Output:
Now we will use DataFrame.dtypes attribute to find out the data type of each column in the given dataframe.
Python3
# return the dtype of each columnresult = df.dtypes # Print the resultprint(result) |
Output:
As we can see in the output, the DataFrame.dtypes attribute has successfully returned the data types of each column in the given dataframe.
