Frank Corso
Solving data challenges for growing companies
I have 2–3 spots available for companies who have data challenges they need solved.
I occasionally write articles on data visualization, data engineering, and data science.
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Maintaining datasets on Kaggle? This tutorial walks you through automating dataset updates using the Kaggle Python API. You’ll learn how to authenticate, format the required data metadata file, and upload new versions programmatically—perfect for integrating into your data pipelines.
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Learn how to get started with Streamlit by building a simple, interactive dashboard from scratch.
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Do you need to extract content or links from a webpage programmatically? You can do so in Python using Requests and Beautiful Soup!
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Heatmaps are a great way to visualize the frequency or ranges of a multi-dimensional dataset. Learn how to create them in Python using Seaborn.
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Using AWS Athena? Learn how to use Python to perform queries to get data from Athena.
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Working with text data for analysis or machine learning? You probably will need to remove stop words. Learn how in this article!
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Looking to visualize connections between different categorical values? Learn how to create a chord diagram!
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Explore the capabilities of AWS Athena, a versatile serverless query engine that empowers you to effortlessly query unstructured, semi-structured, and structured data stored in Amazon S3 using SQL.
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Assessing your classification model’s performance is a critical step. This article explores the key classification metrics such as accuracy, precision, recall, f1 score, and specificity.
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Looking to visualize the data from your Pandas dataframe? Seaborn is a great data visualization library. Learn how it works by creating your first chart!
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One of my favorite MySQL functions that I wished more people knew about is GROUP_CONCAT. This lets you create an aggregated list of values in your queries. Read on to learn how to use it.
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Need to work with CSV files in Python? Learn how to open, read, and write to CSV files!