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@minimaxir
minimaxir / CLAUDE.md
Created January 2, 2026 01:57
Rust CLAUDE.md (20260101)

Agent Guidelines for Rust Code Quality

This document provides guidelines for maintaining high-quality Rust code. These rules MUST be followed by all AI coding agents and contributors.

Your Core Principles

All code you write MUST be fully optimized.

"Fully optimized" includes:

@minimaxir
minimaxir / CLAUDE.md
Created January 2, 2026 01:53
Python CLAUDE.md (20260101)

Agent Guidelines for Python Code Quality

This document provides guidelines for maintaining high-quality Python code. These rules MUST be followed by all AI coding agents and contributors.

Your Core Principles

All code you write MUST be fully optimized.

"Fully optimized" includes:

library(tidyverse)
#Wind speeds from the percentile bands in
#https://weatherspark.com/y/23912/Average-Weather-in-New-York-City-New-York-United-States-Year-Round
#https://weatherspark.com/y/14091/Average-Weather-in-Chicago-Illinois-United-States-Year-Round
#weather.gov wind chill chart at https://www.weather.gov/safety/cold-wind-chill-chart
get_wind_chill = function(temp,wind){
35.74 + .6251*temp - 35.75 * wind^.16 + .4275 * temp * wind^.16
}
library(tidyverse)
CELSIUS = FALSE
heat_index16term = function(T, RH) {
retval = 16.923 + 1.85212 * 1e-1 * T + 5.37941 * RH - 1.00254 * 1e-1 * T *
RH +
9.41695 * 1e-3 * T ^ 2 + 7.28898 * 1e-3 * RH ^ 2 + 3.45372 * 1e-4 *
T ^ 2 * RH - 8.14971 * 1e-4 * T * RH ^ 2 +
1.02102 * 1e-5 * T ^ 2 * RH ^ 2 - 3.8646 * 1e-5 * T ^ 3 + 2.91583 *
snippet drillodbcdistributed
library(DBI)
library(odbc)
library(tidyverse)
DBI::dbConnect(
odbc::odbc(),
driver = "/Library/mapr/drill/lib/libdrillodbc_sbu.dylib",
ConnectionType = "Zookeeper",
AuthenticationType = "No Authentication",
#' ---
#' title: ""
#' author: ""
#' date: ""
#' output:
#' html_document:
#' keep_md: true
#' theme: simplex
#' highlight: monochrome
#' ---
@jakevdp
jakevdp / .block
Last active July 29, 2020 20:03
Interactive Exploration of Seattle Weather
license: MIT
@zross
zross / spatial_example.R
Last active April 6, 2025 11:55
Spatial analysis with R
# An example of spatial analysis with R that involves grabbing data
# from a PostGIS database, joining to tabular data, projecting
# simplifying and creating an interactive map.
# This data is publicly available but requires some processing
# if you want the county boundaries you can find them here:
# cftp://ftp2.census.gov/geo/tiger/TIGER2016/COUNTY/
# The tabular data requires some processing but the raw data
library(tidycensus)
library(plotly)
library(ggplot2) # devtools::install_github("tidyverse/ggplot2")
library(crosstalk)
# Set your Census API key with `census_api_key()` if not already installed
tx <- get_acs(geography = "county",
variables = c(pctcollege = "DP02_0067P",
hhincome = "DP03_0062"),
state = "TX",
library(tidycensus)
library(leaflet)
library(sf)
library(viridis)
options(tigris_use_cache = TRUE)
il1 <- get_acs(geography = "county",
variables = c(hhincome = "B19013_001"),
state = "IL",
geometry = TRUE) %>%