values
This attribute is used to represent the values/data of dataframe in NumPy array form.
Syntax: dataframe_name.values
Python3
# Python program to implement values# attribute in a dataframe objectimport pandas as pd# Creating a 2D dictionary having values as# dictionary objectdict = {"Sales": {'Name': 'Shyam', 'Age': 23, 'Gender': 'Male'}, "Marketing": {'Name': 'Neha', 'Age': 22, 'Gender': 'Female'}}# Creating a data frame objectdata_frame = pd.DataFrame(dict)# printing this data frame on output screendisplay(data_frame)# Implementing values attribute for this data frameprint("NumPy Array form of this DataFrame is:")print(data_frame.values) |
Output:
In this program, we have made a DataFrame from a 2D dictionary having values as dictionary object and then printed this DataFrame on the output screen At the end of the program, we have implemented the “values” attribute as print(data_frame.values) to print all the data of this DataFrame in the form of NumPy array.
Dataframe Attributes in Python Pandas
In this article, we will discuss the different attributes of a dataframe. Attributes are the properties of a DataFrame that can be used to fetch data or any information related to a particular dataframe.
The syntax of writing an attribute is:
DataFrame_name.attribute
These are the attributes of the dataframe:
- index
- columns
- axes
- dtypes
- size
- shape
- ndim
- empty
- T
- values