gshotwell

from shiny import App, render, ui, reactive, module
from htmltools import TagList

app_ui = ui.page_fluid(
    ui.row(
        # add space from the left
        ui.column(3),
        # center with content
        ui.column(
            6,

gshotwell

import datetime
from typing import Dict, List, Optional, Tuple

import astropy.units as u
import matplotlib.dates as mpldates
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import pytz
import suntime

gshotwell

library(tidyverse)
library(lubridate)

df <- tibble(
  dist1 = sort(rnorm(100, 5, 2)), 
  dist2 = sort(rnorm(100, 8, 3)),
  dist4 = sort(rnorm(100, 15, 1)),
  date = seq.Date(from = ymd("2022-01-01"), ymd("2022-04-10"), by = "day")
)

gshotwell

library(tidyverse)

survey <- tibble::tribble(
  ~id,      ~q_1,      ~q_2,      ~q_3,
  1L,    "good",     "bad",  "neutral",
  2L, "neutral",    "good",   "neutral",
  3L,     "bad", "neutral", "neutral",
  4L, "neutral",    "good",    "neutral",
  5L,     "bad",    "good", "neutral",
  6L,     "bad",     "bad",   "neutral"

gshotwell

library(tidyverse)
library(janitor)
library(RcppRoll)
deaths <- read_csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv")

deaths <- deaths %>%
  rename(province_state = `Province/State`,
         country_region = `Country/Region`) %>%
  pivot_longer(-c("province_state", "country_region", "Lat", "Long"),

gshotwell

library(tidyverse)
library(RcppRoll)
library(lubridate)
library(broom)

covid <- read_csv("https://covid.ourworldindata.org/data/owid-covid-data.csv") %>%
  filter(location != "World")

covid <- covid %>%
  group_by(iso_code) %>%

gshotwell

library(tidyverse)
library(rgeos)
library(RcppRoll)
library(rworldmap)

data <- read_csv("https://covid.ourworldindata.org/data/owid-covid-data.csv") %>% 
  filter(location != "World")

plot_df <- data %>% 
  group_by(iso_code) %>% 

gshotwell

select_random <- function(tbl, n_records) {
  tbl <- tbl %>%
    dplyr::mutate(rand = random()) %>%
    dplyr::compute() %>%
    dplyr::arrange(.data$rand) %>%
    dplyr::filter(dplyr::row_number(.data$rand) <= !!n_transactions) %>%
    dplyr::select(-.data$rand)
}

tbl %>% 

gshotwell

#
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
#    http://shiny.rstudio.com/
#

library(shiny)

gshotwell

call <- substitute(ifelse(v == 1,
                          "banana",
                          ifelse(v == 2,
                                 2,
                                 NA))
)

parse_ifelse <- function(call) {
  if (deparse(call[[3]][[1]]) == "ifelse") {
    top_call <- deparse(call[[2]])