--- title: Exploratory Data Analysis for Credit Scoring with Python description: A walkthrough of exploratory data analysis (EDA) on a Kaggle credit scoring dataset with 32,581 observations and 12 variables. Each variable — including... canonical: https://daily.dev/posts/exploratory-data-analysis-for-credit-scoring-with-python-x4a9etnle twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Exploratory Data Analysis for Credit Scoring with Python | daily.dev og:description: A walkthrough of exploratory data analysis (EDA) on a Kaggle credit scoring dataset with 32,581 observations and 12 variables. Each variable — including... og:url: https://daily.dev/posts/exploratory-data-analysis-for-credit-scoring-with-python-x4a9etnle og:image: https://api.daily.dev/og/posts/x4A9eTnle.png og:image:alt: Exploratory Data Analysis for Credit Scoring with Python og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Exploratory Data Analysis for Credit Scoring with Python **[Towards Data Science](https://daily.dev/sources/tds)** · 18 min read · 0 upvotes · 0 comments ## Summary A walkthrough of exploratory data analysis (EDA) on a Kaggle credit scoring dataset with 32,581 observations and 12 variables. Each variable — including borrower age, income, employment length, home ownership, loan grade, interest rate, and prior default history — is analyzed for its distribution and relationship to default risk. Continuous variables are discretized into quartile-based intervals. Key findings include: younger and lower-income borrowers default more, prior default history is a strong predictor, and higher loan grades correlate with lower default rates. Python code using pandas is provided to automate the summary tables and export them to Excel. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Building Robust Credit Scoring Models with Python](https://daily.dev/posts/building-robust-credit-scoring-models-with-python-avvk552gx) · Towards Data Science · 1 upvotes · 0 comments - [From Raw Data to Risk Classes](https://daily.dev/posts/from-raw-data-to-risk-classes-qye2zmgfs) · Towards Data Science · 1 upvotes · 0 comments - [What Student Performance Data Taught Me About Learning with Python](https://daily.dev/posts/what-student-performance-data-taught-me-about-learning-with-python-eclmmw7xf) · Medium · 0 upvotes · 0 comments - [How to use Pandas for data analysis in Python](https://daily.dev/posts/how-to-use-pandas-for-data-analysis-in-python-nxlnwvjde) · InfoWorld · 0 upvotes · 0 comments - [How to Study the Monotonicity and Stability of Variables in a Scoring Model using Python](https://daily.dev/posts/how-to-study-the-monotonicity-and-stability-of-variables-in-a-scoring-model-using-python-qazuozcwo) · Towards Data Science · 0 upvotes · 0 comments --- Tags: [#python](https://daily.dev/tags/python), [#data-science](https://daily.dev/tags/data-science), [#pandas](https://daily.dev/tags/pandas), [#exploratory-data-analysis](https://daily.dev/tags/exploratory-data-analysis) [View this post on daily.dev](https://daily.dev/posts/exploratory-data-analysis-for-credit-scoring-with-python-x4a9etnle) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Exploratory Data Analysis for Credit Scoring with Python","url":"https://daily.dev/posts/exploratory-data-analysis-for-credit-scoring-with-python-x4a9etnle","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/exploratory-data-analysis-for-credit-scoring-with-python-x4a9etnle"},"datePublished":"2026-03-12T16:45:46.951Z","dateModified":"2026-03-12T16:46:17.824Z","description":"A walkthrough of exploratory data analysis (EDA) on a Kaggle credit scoring dataset with 32,581 observations and 12 variables. 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