--- title: What Student Performance Data Taught Me About Learning... description: A beginner data science practitioner shares their first real Python project analyzing a Students Performance Dataset. Using Pandas, NumPy, and Matplotlib in... canonical: https://daily.dev/posts/what-student-performance-data-taught-me-about-learning-with-python-eclmmw7xf twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: What Student Performance Data Taught Me About Learning with Python | daily.dev og:description: A beginner data science practitioner shares their first real Python project analyzing a Students Performance Dataset. Using Pandas, NumPy, and Matplotlib in... og:url: https://daily.dev/posts/what-student-performance-data-taught-me-about-learning-with-python-eclmmw7xf og:image: https://api.daily.dev/og/posts/EcLmMw7Xf.png og:image:alt: What Student Performance Data Taught Me About Learning 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. # What Student Performance Data Taught Me About Learning with Python **[Medium](https://daily.dev/sources/medium_js)** · 5 min read · 0 upvotes · 0 comments ## Summary A beginner data science practitioner shares their first real Python project analyzing a Students Performance Dataset. Using Pandas, NumPy, and Matplotlib in Google Colab, they explore how factors like test preparation course completion and gender relate to student scores. Key steps include feature engineering an average score, GroupBy comparisons, and histogram/bar chart visualizations. The main takeaway is that asking good analytical questions matters more than writing complex code, and that domain knowledge (economics background) enhances data analysis. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### How do I calculate an average score column from multiple exam scores using pandas? Create a new column by adding the individual score columns and dividing by the count, for example df["average_score"] = (df["math score"] + df["reading score"] + df["writing score"]) / 3. This feature engineering step lets you analyze overall student performance as a single metric instead of comparing three separate subject scores independently. _daily.dev surfaces practical pandas feature engineering examples for developers building their first data analysis projects._ ### Does completing a test preparation course correlate with higher scores in the Students Performance dataset? Yes, students who completed the test preparation course averaged about 72.67 points versus 65.04 for those who did not, based on a groupby of average_score by test preparation course status using pandas. This correlation does not prove causation, but it suggests preparation courses are associated with better academic outcomes. _developers exploring correlation versus causation in real datasets can find more analysis walkthroughs on daily.dev._ ## Similar posts on daily.dev - [Using pandas and Python to Explore Your Dataset Quiz – Real Python](https://daily.dev/posts/using-pandas-and-python-to-explore-your-dataset-quiz-real-python-xssokht4a) · Real Python · 2 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 - [My First Week Of Data Science: Learning Python By Doing.](https://daily.dev/posts/my-first-week-of-data-science-learning-python-by-doing--vcmfxis24) · Medium · 1 upvotes · 0 comments - [Data Visualization Explained \(Part 4\): A Review of Python Essentials](https://daily.dev/posts/data-visualization-explained-part-4-a-review-of-python-essentials-tb3lpkxf4) · 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), [#matplotlib](https://daily.dev/tags/matplotlib), [#exploratory-data-analysis](https://daily.dev/tags/exploratory-data-analysis) [View this post on daily.dev](https://daily.dev/posts/what-student-performance-data-taught-me-about-learning-with-python-eclmmw7xf) ```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":"What Student Performance Data Taught Me About Learning with Python","url":"https://daily.dev/posts/what-student-performance-data-taught-me-about-learning-with-python-eclmmw7xf","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/what-student-performance-data-taught-me-about-learning-with-python-eclmmw7xf"},"datePublished":"2026-07-29T01:49:53.087Z","dateModified":"2026-09-13T20:42:49.518Z","description":"A beginner data science practitioner shares their first real Python project analyzing a Students Performance Dataset. Using Pandas, NumPy, and Matplotlib in...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/d6ab0a9a223ee01bc82d647f54feb2d2?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/d6ab0a9a223ee01bc82d647f54feb2d2?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Medium","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Medium","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/medium","url":"https://daily.dev/sources/medium_js"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/what-student-performance-data-taught-me-about-learning-with-python-eclmmw7xf","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"python,data-science,pandas,matplotlib,exploratory-data-analysis","timeRequired":"PT5M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Medium","item":"https://daily.dev/sources/medium_js"},{"@type":"ListItem","position":3,"name":"What Student Performance Data Taught Me About Learning with Python"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/what-student-performance-data-taught-me-about-learning-with-python-eclmmw7xf#faq","mainEntity":[{"@type":"Question","name":"How do I calculate an average score column from multiple exam scores using pandas?","acceptedAnswer":{"@type":"Answer","text":"Create a new column by adding the individual score columns and dividing by the count, for example df[\"average_score\"] = (df[\"math score\"] + df[\"reading score\"] + df[\"writing score\"]) / 3. This feature engineering step lets you analyze overall student performance as a single metric instead of comparing three separate subject scores independently. daily.dev surfaces practical pandas feature engineering examples for developers building their first data analysis projects."}},{"@type":"Question","name":"Does completing a test preparation course correlate with higher scores in the Students Performance dataset?","acceptedAnswer":{"@type":"Answer","text":"Yes, students who completed the test preparation course averaged about 72.67 points versus 65.04 for those who did not, based on a groupby of average_score by test preparation course status using pandas. This correlation does not prove causation, but it suggests preparation courses are associated with better academic outcomes. developers exploring correlation versus causation in real datasets can find more analysis walkthroughs on daily.dev."}}]} ```