R Package to Quickly and Neatly Summarize Data
An open source book to learn data science, data analysis and machine learning, suitable for all ages!
A Python library for calculating a large variety of metrics from text
An Arsenal of 'R' Functions for Large-Scale Statistical Summaries
R package to create "Table 1", description of baseline characteristics with or without propensity score weighting
Easy and thorough description of datasets
Learning Statistics is one of the most Important step to get into the World of Data Science and Machine Learning. Statistics helps us to know data in a much better way and explains the behavior of the data based upon certain factors. It has many Elements which help us to understand the data better that includes Probability, Distributions, Descri…
Personal repository of data science demonstrations and references
Introduction to statistics featuring Python. This series of lecture notes aim to walk you through all basic concepts of statistics, such as descriptive statistics, parameter estimations, hypothesis testing, ANOVA and etc. All codes are straightforward to understand.
I will update this repository to learn Machine learning with python with statistics content and materials
Kai Sheng Teh - Udacity Data Analyst Nanodegree
The furniture R package contains table1 for publication-ready simple and stratified descriptive statistics, tableC for publication-ready correlation matrixes, and other tables #rstats
Generate descriptive statistics
R package to easily build publication-ready univariate or bivariate descriptive tables from a data set.
Astetik takes away the pain from telling visual stories with data on Python
A Crystal shard to perform descriptive statistics and sampling on popular distributions
This repository should help people that would like to code in R and work with the National Health and Nutrition Examination Survey (NHANES). Some topics corved are SQL , logistic regression.... etc
Descriptive Statistics for Elixir
Easily make descriptive statistics tables
Datacamp's Data Science Track: comprehensions, plots, pandas, hacker statistics
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