Pandas Dataframe vs Numpy Array
In this post, you will learn about which data structure to use between Pandas Dataframe and Numpy Array when working with Scikit Learn libraries. As a data scientist, it is very important to understand the difference between Numpy array and Pandas Dataframe and when to use which data structure.
Here are some facts:
Here is the code which can be used to convert Pandas dataframe to Numpy array:
import pandas as pd
# Load data as Pandas Dataframe
df = pd.read_csv("...")
# Convert dataframe to Numpy array
df.values
Here is what will get printed:
In this post, you learned about difference between Numpy array and Pandas Dataframe. Simply speaking, use Numpy array when there are complex mathematical operations to be performed. Use Pandas dataframe for ease of usage of data preprocessing including performing group operations, creation of Matplotlib plots, rows and columns operations. As a matter of fact, one could use both Pandas Dataframe and Numpy array based on the data preprocessing and data processing needs.
Large language models (LLMs) have fundamentally transformed our digital landscape, powering everything from chatbots and…
As Large Language Models (LLMs) evolve into autonomous agents, understanding agentic workflow design patterns has…
In today's data-driven business landscape, organizations are constantly seeking ways to harness the power of…
In this blog, you would get to know the essential mathematical topics you need to…
This blog represents a list of questions you can ask when thinking like a product…
AI agents are autonomous systems combining three core components: a reasoning engine (powered by LLM),…
View Comments
Thanks for this article! it helped a lot!