Derek Willis dwillis

I hereby claim:

To claim this, I am signing this object:

brew install libspatialite

geojson-to-sqlite toxmap.db hotspots hotspot_perimeters_for_data_store.geojson --spatialite

datasette toxmap.db --load-extension=spatialite

	import os
	import csv
	from dateutil.parser import parse
	from slack import WebClient
	from slack.errors import SlackApiError

	slack_token = os.environ["SLACK_API_TOKEN"]
	client = WebClient(token=slack_token)

	march_27 = parse('3/27/2022').date()

	# create dataframe of all shootings by gender

	all_police_shootings_by_gender <- fatal_police_shootings %>%
	group_by(gender) %>%
	summarise(count=n()) %>%
	arrange(desc(count))

	# create separate dataframes for each gender
	all_shootings_men <- all_police_shootings_by_gender %>%
	filter(gender == 'M')

	Sample template for basic filtering, mutate and group_by with count

	```{r}

	my_result <- original_data %>%
	filter(some_column == "some value") %>%
	mutate(some_column=str_to_title(some_column)) %>%
	group_by(some_column) %>%
	summarise(new_aggregate = n()) %>%
	arrange(desc(new_aggregate))

	allegany_sums_all <- allegany_athletics %>%
	group_by(county, year) %>%
	summarise(boys_total = sum(boys_participants), girls_total = sum(girls_participants)) %>%
	select(county, year, boys_total, girls_total)

	allegany_sums_without_cau <- allegany_athletics %>%
	filter(is.na(type)) %>%
	group_by(county, year) %>%
	summarise(boys_without_cs = sum(boys_participants), girls_without_cs = sum(girls_participants)) %>%
	select(county, year, boys_without_cs, girls_without_cs)

	html <- read_html("https://merrill.umd.edu/about/faculty-and-staff")

	# get faculty/staff names
	names <- html %>% html_nodes(".card-title") %>% html_text()

	length(faculty_staff)

	faculty_staff[1]

	# get titles

	library(tidyverse)
	library(stringr)
	library(fs)

	results <- data.frame()

	years <- c('2021','2020')

	for (year in years) {
	data_dir <- str_c("/Users/dwillis/code/wbb/fiba/", year)