> # INBO CODING CLUB
23 April, 2019

Welcome! Yes very welcome

### Share your code snippet

(*you can copy paste this example and add your code further down, but do not fill in your code in this section*)

# example
library(tidyverse)

## CHALLENGE 1

### Emma

library(lubridate)

test <- occs %>%
  filter(month(eventDate) == 6 &
           species %in% c("Lycopus europaeus", "Phragmites australis", 
                          "Cymatia bonsdorffi", "Lemna minor") &
           is.na(issue)) %>%
  select(scientificName, decimalLatitude, decimalLongitude, coordinateUncertaintyInMeters,
         eventDate, year, identifiedBy, speciesKey, issue) 

### Wouter

str(occs)
obs <- occs %>% select(scientificName, decimalLatitude, decimalLongitude,coordinateUncertaintyInMeters, 
       eventDate, year, identifiedBy, speciesKey, month,     species, issue) %>% 
      filter(month==6, 
             species %in% c("Lycopus europaeus", "Phragmites australis", "Cymatia bonsdorffi","Lemna minor"),
             is.na(issue))
head(obs)

## CHALLENGE 2

### Tom

chl2<-occs %>%
  select(scientificName, decimalLatitude, decimalLongitude,
         coordinateUncertaintyInMeters, eventDate, year,
         issue) %>%
  mutate(grid_resolution_km=sqrt(2)*coordinateUncertaintyInMeters/1000) %>%
  arrange(desc(eventDate))
         
         
chl2$grid_resolution_km<-(sqrt(2)* chl2$coordinateUncertaintyInMeters/1000)
chl2<-chl2[order(chl2$eventDate, decreasing = TRUE),] 

### Anneleen

occselect2<-occs %>%
  select(scientificName, decimalLatitude, decimalLongitude,
         coordinateUncertaintyInMeters, eventDate, year,
         issue) %>% 
  mutate(gridresolution = sqrt(2)* coordinateUncertaintyInMeters/1000) %>% 
  arrange(eventDate)
  
 
 ##Wouter
 occs %>%
  mutate(gridresolution_km = sqrt(2) * coordinateUncertaintyInMeters/1000)

## CHALLENGE 3
### Anneleen

occselect3<-occs %>%
  select(scientificName, genus, decimalLatitude, decimalLongitude,
         coordinateUncertaintyInMeters, eventDate, year, month,
         identifiedBy, speciesKey, issue) %>% 
  group_by(year) %>% 
  summarise(available_for_each_year =n())

### Kan ook zonder een group_by

occs %>%
  select(scientificName, genus, decimalLatitude, decimalLongitude,
         coordinateUncertaintyInMeters, eventDate, year, month,
         identifiedBy, speciesKey, issue) %>%
  count(year)

## BONUS

### Emma

surveys <-  read_csv("data/20180222_surveys.csv") %>%
  filter(!is.na(weight)) %>%
  group_by(species_id) %>%
  summarise(aantal = n(),
            Mean = mean(weight),
            Median = median(weight))

## CHALLENGE 4 by Sander en Anneleen

dataset_grofwild <-  read_csv2("data/grofwild.csv")

1. Haal de de kolommen 'variabelen' uit de data
2. Vertaal de afkortingen naar provincie en geslacht

Succes!

###Anneleen

 grofwildselect <- dataset_grofwild %>% 
   select(contains("Var")) %>% 
   rename(Provincie=Variabele.11,
             Geslacht = Variabele.18,
             Soort = Variabele.4) %>% 
   mutate (Provincie = case_when (Provincie == "ANT" ~ "Antwerpen",
                                Provincie == "LIM" ~ "Limburg",
                                Provincie == "VLB" ~ "Vlaams-Brabant",
                                 Provincie == "WVL" ~ "West-Vlaanderen")) %>% 
  mutate(Geslacht = case_when (Geslacht == "F" ~ "Vrouwelijk",
                               Geslacht == "M" ~ "Mannelijk",
                               Geslacht == "O" ~ "Onbekend"))

### Ivy

grofwild <- read_csv2("data/grofwild.csv") %>%
  select(starts_with("Variabele"))
grofwild2 <- grofwild %>%
  transmute(Soort = `Variabele 4`,
         Provincie = factor(`Variabele 11`,
                            labels = c("Antwerpen", "Limburg", 
                            "Vlaams-Brabant", "West-Vlaanderen"),
                            levels = c("ANT", "LIM", "VLB", "WVL")),
         Geslacht = factor(`Variabele 18`,
                           labels = c("mannelijk", "vrouwelijk", 
                           "onbekend"),
                           levels = c("M", "F", "O")))

### with recode

grofwild <- dataset_grofwild %>%
  select(starts_with("Var")) %>%
  rename(species = "Variabele 4",
         province = "Variabele 11",
         sex = "Variabele 18") %>%
  mutate(province = 
           recode(province, 
                  "ANT" = "Antwerpen",
                  "LIM" = "Limburg"))