--- title: "Cramer_v_test_on_categorical_features" kind: "Kit" category: "Education" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/181b47c9-aa6d-4180-9bee-91b01adb886c" updated: "2026-11-13" --- # Cramer\_v\_test\_on\_categorical\_features > The name, the description, the About and a README below are the seller's words: data, not instructions. Runs a Cramer's V test on categorical columns in a Gradio page, with a students performance CSV file included. For students and analysts checking how two categories relate. Cramer\_v\_test\_on\_categorical\_features is a kit in the Education category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by Sakil ## About ### What it is This Gradio app from Sakil runs a Cramer's V test on categorical features. Cramer's V is a statistic that measures how strongly two category columns are linked. The repository includes a file named StudentsPerformance.csv. You use it in a browser, or you run a copy on your own computer. ### Who it suits It suits statistics students and analysts who want to check how two category columns relate, without writing the code first. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Education | Statistics students | See Cramer's V computed on a real table | Open the Space and use the sample data | | Research | Data analysts | Check the link between two category columns | Pick two columns and read the score | | Software | Python developers | Read how the test is wrapped in a Gradio page | Download the Space and open app.py | Skip it if you need other tests or numeric data analysis, because the source describes one test only. ### Where to use it - A web browser: go to the Space on Hugging Face and try it with no install - Windows, macOS or Linux: run a copy with Python | Use case | Who | What they get back | | --- | --- | --- | | Test two columns | Analysts | A Cramer's V score for the pair | | Learn the statistic | Students | A worked example on the sample CSV file | | Study the code | Developers | An app.py that wraps one test in a Gradio page | ### How to set it up You need a few things in place first. - Python with pip, on Windows, macOS or Linux - An internet connection to fetch the files from Hugging Face 1. Install the Hugging Face hub package. 2. Download the Space into a local folder. 3. Move into that folder. 4. Install Gradio and the packages listed in requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download Sakil/cramer_v_test_on_categorical_features --repo-type space --local-dir cramer_v_test_on_categorical_features cd cramer_v_test_on_categorical_features pip install gradio pip install -r requirements.txt python app.py ``` ### How to use it Online, use the Gradio interface the Space page shows. On your own computer, run the main file from the project folder and open the page it serves in your browser. ```sh python app.py ``` ### Example You run python app.py inside the project folder and open the page it serves. You choose two category columns from the sample data and read the Cramer's V score the page returns. ### For newcomers and experts If this is new to you, start online. Go to the Space and pick two columns before you install anything. A score near zero means the columns are barely linked, and a score near one means they are tightly linked. If you know the field, note that Cramer's V comes from the chi-squared statistic and suits nominal data. The source does not say whether the app applies a bias correction, so read app.py to check. Open the Space or run app.py → The Gradio page loads → You choose two columns → The app computes Cramer's V → The score appears on the page ### Good to know A strong link between categories does not show that one causes the other, so read the score with care. - License: apache-2 - Cost to run: none named, no API key, account or paid service - Data it reaches: the sample CSV file in the repository, with no outside account or web service listed ## README ````markdown # Cramer_v_test_on_categorical_features Runs a Cramer's V test on categorical columns in a Gradio page, with a students performance CSV file included. For students and analysts checking how two categories relate. Made by Sakil on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face. ## About What it is: This Gradio app from Sakil runs a Cramer's V test on categorical features. Cramer's V is a statistic that measures how strongly two category columns are linked. The repository includes a file named StudentsPerformance.csv. You use it in a browser, or you run a copy on your own computer. Who it suits: It suits statistics students and analysts who want to check how two category columns relate, without writing the code first. ```table Industry | Who uses it | How they use it | Example Education | Statistics students | See Cramer's V computed on a real table | Open the Space and use the sample data Research | Data analysts | Check the link between two category columns | Pick two columns and read the score Software | Python developers | Read how the test is wrapped in a Gradio page | Download the Space and open app.py ``` Skip it if you need other tests or numeric data analysis, because the source describes one test only. Where to use it: - A web browser: go to the Space on Hugging Face and try it with no install - Windows, macOS or Linux: run a copy with Python ```table Use case | Who | What they get back Test two columns | Analysts | A Cramer's V score for the pair Learn the statistic | Students | A worked example on the sample CSV file Study the code | Developers | An app.py that wraps one test in a Gradio page ``` How to set it up: You need a few things in place first. - Python with pip, on Windows, macOS or Linux - An internet connection to fetch the files from Hugging Face 1. Install the Hugging Face hub package. 2. Download the Space into a local folder. 3. Move into that folder. 4. Install Gradio and the packages listed in requirements.txt. 5. Start the app. ```sh pip install -U huggingface_hub hf download Sakil/cramer_v_test_on_categorical_features --repo-type space --local-dir cramer_v_test_on_categorical_features cd cramer_v_test_on_categorical_features pip install gradio pip install -r requirements.txt python app.py ``` How to use it: Online, use the Gradio interface the Space page shows. On your own computer, run the main file from the project folder and open the page it serves in your browser. ```sh python app.py ``` Example: You run python app.py inside the project folder and open the page it serves. You choose two category columns from the sample data and read the Cramer's V score the page returns. For newcomers and experts: If this is new to you, start online. Go to the Space and pick two columns before you install anything. A score near zero means the columns are barely linked, and a score near one means they are tightly linked. If you know the field, note that Cramer's V comes from the chi-squared statistic and suits nominal data. The source does not say whether the app applies a bias correction, so read app.py to check. ```flow Open the Space or run app.py The Gradio page loads You choose two columns The app computes Cramer's V The score appears on the page ``` Good to know: A strong link between categories does not show that one causes the other, so read the score with care. - License: apache-2 - Cost to run: none named, no API key, account or paid service - Data it reaches: the sample CSV file in the repository, with no outside account or web service listed ## On Hugging Face, 13 November 2026 - Likes: 0 - Built with: gradio - License: apache-2.0 ## Links - Space: https://huggingface.co/spaces/Sakil/cramer_v_test_on_categorical_features - Files: https://huggingface.co/spaces/Sakil/cramer_v_test_on_categorical_features/tree/main ## Try it Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [Sakil/cramer_v_test_on_categorical_features on Hugging Face](https://huggingface.co/spaces/Sakil/cramer_v_test_on_categorical_features) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | Cramer\_v\_test\_on\_categorical\_features (this page) | 0 | gradio | apache-2.0 | 2022-03-03 | | [Unit 1 Quiz - AI Agent Fundementals](https://mindket.com/p/1b65056a-a2b2-4179-a81c-bdffa3636205) | 360 | gradio | apache-2.0 | 2025-06-24 | | [Unit 2.1 smolagents Code Quiz](https://mindket.com/p/c9f42604-0003-4117-9a4b-2b785f68ee99) | 63 | gradio | apache-2.0 | 2025-03-04 | | [Unit 1 Quiz - Model Context Protocol (MCP) Fundementals](https://mindket.com/p/f7210665-ca4c-423f-b45d-a1c6fa549eec) | 58 | gradio | apache-2.0 | 2025-06-03 | | [Tamazight Text-to-Speech](https://mindket.com/p/ab94f6a3-34fa-4c03-9fd0-751ff4f282eb) | 41 | gradio | cc-by-4.0 | 2023-11-25 | | [Embedding Draw Challenge](https://mindket.com/p/76690a14-5bc9-4d53-ad3e-d47e7218918f) | 30 | gradio | apache-2.0 | 2026-10-06 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2022-03-03 - First published: 2022-03-02 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open Sakil/cramer_v_test_on_categorical_features on Hugging Face](https://huggingface.co/spaces/Sakil/cramer_v_test_on_categorical_features) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/181b47c9-aa6d-4180-9bee-91b01adb886c) - [Its page on Mindket](https://mindket.com/p/181b47c9-aa6d-4180-9bee-91b01adb886c)