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import aiohttp | |
import asyncio | |
http_status_codes = { | |
100: "Continue", | |
101: "Switching Protocols", | |
102: "Processing", | |
200: "OK", | |
201: "Created", | |
202: "Accepted", |
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from jinja2 import Template | |
from jinja2 import Environment, meta | |
class Question: | |
"""This class reprsents a question sent to an LLM (or human). | |
It uses the jinja2 templating language to generate the prompt. | |
For details on jinja2: https://jinja.palletsprojects.com/en/3.0.x/ | |
This templating language gives us lots of flexibility in how we ask questions. | |
""" | |
def __init__(self, template_string): |
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# Find all your R files & get just the package names, uniquely | |
find ../analysis/ -name *R -print0 | xargs -0 grep -h 'library*' | sed 's/library//g' | sed 's/#//g' | sed 's/ //g' | sort | uniq|\ | |
sed 's/(//g' | sed 's/)//g' > package_list.txt | |
# Install each package | |
cat package_list.txt | xargs -I {} Rscript -e 'install.packages("{}")' |
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#!/usr/bin/Rscript --vanilla | |
suppressPackageStartupMessages({ | |
library(magrittr) | |
library(dplyr) | |
library(foreign) | |
library(plm) | |
library(reshape2) | |
library(stargazer) | |
library(ggplot2) |
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project_name = hot_towel | |
ts := $(shell /bin/date "+%Y-%m-%d---%H-%M-%S") | |
params = | |
# DONE | |
params += params_exp_details.tex | |
params_exp_details.tex: ../analysis/params_exp_details.R | |
cd ../analysis && ./params_exp_details.R |
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library(XML) | |
library(ggplot2) | |
df <- readHTMLTable("http://projects.dailycal.org/paychecker/departments/")[[1]] | |
DeMoney <- function(x) as.numeric(gsub(",", "", gsub("\\$", "", as.character(x)))) | |
money.columns <- c("All", "Professor", "Associate professor", "Assistant professor", | |
"Lecturer") |
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library(geofacet) # my forked version | |
library(ggplot2) | |
library(jsonlite) | |
library(ggrepel) | |
# grab top cities | |
cities <- fromJSON("https://gist.githubusercontent.com/Miserlou/c5cd8364bf9b2420bb29/raw/2bf258763cdddd704f8ffd3ea9a3e81d25e2c6f6/cities.json") | |
n <- 50 | |
x <- cities$longitude[1:n] |
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library(lfe) | |
library(stargazer) | |
set.seed(6152011) | |
# Number of cities | |
L <- 1000 | |
# Number of industries | |
K <- 3 |
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SimExperiment <- function(num.groups, sample.size, beta, randomize.by.group = FALSE){ | |
"Simulate running an analysis of the experiment with linear regression" | |
df <- CreateClusteredData(num.groups, sample.size, beta, randomize.by.group = randomize.by.group) | |
m <- lm(y ~ trt, data = df) | |
c(as.numeric(coef(m)[2]), as.numeric(sqrt(diag(vcov(m))[2]))) | |
} |
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CreateClusteredData <- function(num.groups, sample.size, beta, randomize.by.group = FALSE){ | |
individual <- 1:sample.size # index for individuals | |
group <- sample(1:num.groups, size = sample.size, replace = TRUE) # randomly assign everyone to a group | |
group.effect <- rnorm(num.groups) # create a group-specific effect | |
eta <- group.effect[group] # give each individual their group-specific effect | |
epsilon <- rnorm(sample.size) # given each individual an individual-specific effect | |
if (randomize.by.group){ | |
group.trt.assignment <- rbinom(num.groups, 1, 0.5) | |
trt <- group.trt.assignment[group] | |
} else { |
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