GPT 4o + Canvas + o1 preview — Data Analysis Just Took a Quantum Leap!

Author(s): Gencay I.

Originally published on Towards AI.

Let’s Analyze the Dataset by using this combination

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OpenAI has been consistently publishing different models to meet our diverse needs. But what if we used them for the same purposes in different windows?In this example, we will unlock the full potential of their models for data analysis. To do that, let’s use a real-life dataset from Kaggle.

Reference

For this article, we are going to use the International football results dataset. You can see the Kaggle link to this dataset here.

After downloading the dataset, you’ll see three different datasets. You can also load it using code.

import kagglehub# Download latest versionpath = kagglehub.dataset_download("martj42/international-football-results-from-1872-to-2017")print("Path to dataset files:", path)

After running this code, you will see that this will be loaded to your local environment. Use the following code to see where it has been loaded;

files = os.listdir(path)print("Files in dataset:", files)

Here is my output.

SS of the output

It is time to load these into data frames, so let’s start Data exploration. Here is the code to load the dataset.

import pandas as pdimport osimport kagglehub# Download the latest version of the datasetpath = kagglehub.dataset_download("martj42/international-football-results-from-1872-to-2017")# Specify file namesfiles = ['goalscorers.csv', 'shootouts.csv', 'results.csv']#… Read the full blog for free on Medium.

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Published via Towards AI