example_stats
OfficialQuick stats on plain Python lists without numpy
Data & Analytics#data analysis#descriptive statistics#number list#z-score normalization#Pearson correlation
AuthorPKU-YuanGroup
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill simplifies the process of calculating descriptive statistics (mean, standard deviation, median, quantile, z-score normalization, and Pearson correlation) on plain Python number lists without relying on numpy or pandas.
Core Features & Use Cases
- Summary Statistics: Generate a summary report of a dataset with mean, standard deviation, median, minimum, maximum, and more.
- Quantiles: Compute any arbitrary quantile (0-1) from a dataset.
- Normalization: Standardize values with z-score normalization.
- Correlation: Calculate the Pearson correlation coefficient between two datasets.
- Use Case: For a given dataset, quickly compute the mean and standard deviation to understand the central tendency and spread of the data.
Quick Start
Calculate the mean and standard deviation for a list of numbers: mean([4, 8, 15, 16, 23, 42])
Dependency Matrix
Required Modules
None requiredComponents
scripts
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: example_stats Download link: https://github.com/PKU-YuanGroup/OpenAI4S/archive/main.zip#example-stats Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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