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# Functional Programming 
# ID529 

# Topics to cover 
# 
#  - sapply, apply family 
#  - purrr::map 
#  - summarize 
#  - stratified models
# 

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# Let's Review

# We circulated a survey about what would be the most useful material for us to
# review and revisit, as well as if there are any questions that would be useful
# for us to go over together.

# Overall topics to try to cover: 
# 
#   - dplyr and data manipulation 
#   - color in ggplot2 

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# ID529 Core Concepts Script 

# This script covers the following skills:
#   - Installing packages 
#   - Reading csv data in with readr::read_csv
#   - Using dplyr for group_by and summarize
#   - Creating factors, setting reference levels
#   - Creating plots with ggplot2 and saving them 
#   - Fitting a model
#   - Reporting on a model with gtsummary

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#' Create Encrypted Files
create_encrypted_height_weight_medications <- function() {

  # load files to be encrypted
  dfs <-
    list(
      file1 = "sensitive_data/file1.xlsx",
      file2 = "sensitive_data/file2.xlsx",
      file3 = "sensitive_data/file3.xlsx"
    ) %>% purrr::map(readxl::read_excel)

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library(raster)
library(sf)
library(mapview)
library(janitor)
library(tidyverse)
library(RColorBrewer)

# google: get shapefiles for states of india in r 
# results: 
#   - https://rstudio-pubs-static.s3.amazonaws.com/435552_5656a7fe6636474fb0f8d4222d79db2c.html 

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library(sf)
library(ggplot2)

nc <- st_read(system.file("shapes/sids.shp", package="spData")[1], quiet=TRUE)

nc %>% 
  ggplot(aes(fill = AREA)) + 
  geom_sf(size = 0.05, color = 'white') + 
  scale_fill_gradientn(
    colors = c("#DA8907", "#ECCD00", "white", "#62AEDC", "#203856"))

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# dependencies
library(tidycensus)
library(leaflet)
library(magrittr)
library(dplyr)
library(tidyr)
library(stringr)
library(ggplot2)
library(leafpop)
library(mapview)