Skip to content
Pythoneo: Python Programming, Seaborn & Plotly Tutorials

Master Python: How-To Tutorials & Solutions for Coders

  • Home
  • Privacy Policy
  • About
  • Cookie Policy
  • Home
  • Privacy Policy
  • About
  • Cookie Policy
  • statistics

    How to Calculate Deciles in Python Using statistics.quantiles (Decile Definition and Example)

    March 2, 2021

    Deciles divide a dataset into ten equal parts, each representing 10% of the data. For example, the first decile represents the point below which 10% of the data falls, the second decile represents the point below which 20% of the data falls, and so on. Let’s see how to calculate deciles in Python using the statistics.quantiles function with n=10, which returns the cut points that split your data into ten equal parts.

    Continue Reading

Resources

  • Matplotlib Master Hub + Recipes
  • OpenCV Master Hub + Recipes
  • Seaborn Master Hub + Recipes
  • Tkinter Master Hub + Patterns
  • SciPy Optimize Cookbook (minimize, least_squares, linprog)
  • Plotly Maps & Geo Cookbook
  • Paramiko Master Hub + Production Cookbook
  • NumPy Master Hub + Cheatsheets
  • Ultimate Python Cheatsheet + Gotchas
  • Django Master Hub + Recipes

Tags

array axis button calculations chart column conversion count data type dimension draw dtype empty error fill float generate grid GUI image index integer list matrix max mean min mode multiply normal distribution number pie plot random reshape rotate round rows size string sum test text time zero

Categories

  • bokeh (6)
  • Django (13)
  • FastAPI (3)
  • matplotlib (13)
  • numpy (121)
  • OpenCV (7)
  • Pandas (6)
  • paramiko (63)
  • Pillow (6)
  • Plotly (23)
  • Python (74)
  • Scipy (9)
  • Seaborn (25)
  • statistics (6)
  • Tkinter (34)
  • turtle (2)

RSS RSS

  • Integrating Large Language Models in Python: From API Calls to Production Deployment
  • Testing FastAPI Applications: Complete Guide with Pytest, Coverage, and Best Practices
  • Deploying Python Applications to Production: Docker, CI/CD, Monitoring and Scaling
  • FastAPI Authentication & Authorization: JWT, OAuth2, and RBAC
  • FastAPI Complete Guide: Building Production APIs
  • Plotly Scatter Plot Tutorial: Interactive Data Exploration
  • Python Data Visualization Best Practices: Creating Effective Charts
  • Matplotlib vs Seaborn: Which Library Should You Use?
  • Seaborn Pair Plots: Multivariate Relationship Visualization
  • Django Messages Framework: User Feedback Done Right
Graceful Theme by Optima Themes