v0.4.0New: time series, EDA, imputation
Stats
LibX
A powerful, modern statistical analysis library for Python — from descriptive to computational statistics, including time series, EDA and imputation. The real library runs in your browser on the playground: no install required.
$pip install statslibx
10+Modules
90+Methods
6Datasets
v0.4.0Version
ViewXIntegration
Built-in Modules
Ten modules covering the full analysis workflow — from quick summaries to time series and automatic EDA.
Quick Start
Get up and running with just a few lines of code.
example.py
python
from statslibx import DescriptiveStats, InferentialStats
from statslibx.datasets import load_iris
data = load_iris()
ds = DescriptiveStats(data)
print(ds.summary())
print(ds.correlation(method='pearson'))
inf = InferentialStats(data)
ci = inf.confidence_interval(column='sepal_length', statistic='mean')Built-in Datasets
Ready-to-use datasets for immediate analysis and experimentation.
iris.csv
penguins.csv
titanic.csv
sp500_companies.csv
course_completion.csv
Cocoa_Bubbles_Investment_Nigeria_Ghana_1980_2023.xlsx
Ready to Explore?
The playground loads the real statslibx in your browser — full analysis, inline plots and bundled datasets, zero installation.
Open Playground