data-analysis   2020

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StatsModels: Statistics in Python — statsmodels 0.9.0 documentation
Provides classes and functions for the estimation statistical models, as well as for conducting statistical tests, and statistical data exploration. Compatible with Pandas dataframes.
python  statistics  data-analysis  pandas 
7 days ago by mjlassila
A Guide to Guides: Axes & Legends in Vega / Observable
A central concern of data visualization is the design of visual encodings: selecting graphical marks (bars, points, lines, ...) and visual attributes (encoding channels such as position, color, size, shape, ...) to represent data dimensions. Visual encodings can be expressed as scale functions that map data values to visual values such as pixel positions, RGB color values, etc. Using the building blocks of marks, encoding channels, and scales, a wide range of chart types can be elegantly expressed.
data-analysis  visualisation  design  graphics  d3  js 
5 weeks ago by kmt
Associate Data Scientist at BuzzFeed who loves making pretty charts and blogging about them at!
No gimmicks. No proprietary software. No datasets that everyone else has already analyzed.

Data Science Unscripted is a new series where I livestream data analysis and visualization, skipping no steps. Data science is a field with many tradeoffs at every step that can't be accurately conveyed with a blog post, and this livestream intends to show more transparency into the data process.

I intend to do a stream every weekend (depending on demand) doing work with R and Python, with all videos saved as a VOD in case you miss it. Follow my Twitch channel for more updates!
python  r  data-science  data-analysis  datasets  livestream  twitch  patreon 
5 weeks ago by Spark
Python Data Science Handbook: full text in Jupyter Notebooks
Collection of Jupyter notebooks containing runnable code and full text of the book.
python  data-analysis  pandas  research  analytics 
6 weeks ago by mjlassila
CRAN - Package Hmisc
Contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX and html code, and recoding variables.
R  Packages  DataScience  Data-Analysis 
7 weeks ago by walecain

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