README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```
# airparis

<!-- badges: start -->
<!-- badges: end -->

Package `airparis` is providing a small set of functions to access data about air quality in Ile-de-France 
provided by [Airparif](https://www.airparif.asso.fr/). 

```{r echo=FALSE, fig.height=2, message=FALSE}
library(airparis)
library(tidyverse)
library(ggiraph)
library(lubridate)
library(glue)

change_dayinweek <- function(x){
  x[x %in% 1] <- 8
  x
}

data <- read_atmo() %>% 
  mutate(isoweek = isoweek(date_time),
         isoyear = isoyear(date_time),
         weekday = change_dayinweek(wday(date_time)),
         daylabel = weekdays(date_time), 
         classification = cut( score, breaks = c(0, 4.5, 7.5, Inf), labels = c("Bon", "Mediocre", "Mauvais")),
         tooltip = glue("{daylabel} {date_time}\nindice {score}\nclassification: {classification}")
         ) 

weektoadd <- data %>% filter(isoyear == min(isoyear)) %>% 
  arrange(desc(isoweek)) %>% 
  slice(1) %>% pull(isoweek)

data <- mutate(
  data, 
  weekid = case_when(
    isoyear == min(isoyear) ~ isoweek,
    TRUE ~ isoweek + weektoadd)
  )

P <- ggplot(data, aes(weekid, weekday, fill = classification, tooltip = tooltip)) + 
  geom_tile_interactive(colour = "white") + 
  coord_equal() + 
  scale_y_reverse() + 
  scale_fill_manual_interactive(name = "",
    values = c("Bon" = "#84bf75", "Mediocre" = "#f29400", "Mauvais" = "#d82517"),
    tooltip = c("Bon" = "1 <= indice <= 4", "Mediocre" = "5 <= indice <= 7", "Mauvais" = "8 <= indice <= 10")) + 
  theme_void() + 
  theme(legend.position = "bottom", 
        legend.key.size = unit(0.25, "cm") ) +
  labs(title = "ATMO index")

girafe(ggobj = P, width_svg = 6, height_svg = 2) %>% 
  girafe_options(opts_zoom(max = 3), opts_toolbar(position = "top"))
```



Users can retrieve hourly and daily data measured in Ile-de-France with function 
`read_measures()`. The following pollutants are available:

* `o3`: ozone
* `pm10`: Particulate matter with a diameter of 10 micrometers or less
* `pm25`: Particulate matter with a diameter of 2.5 micrometers or less
* `nox`: Nitrogen oxide
* `no2`: Nitrogen dioxide

```{r}
library(airparis)
read_measures(pollutant = "pm10", station_id = "4181",
  dt_start = as.Date("2019-06-01"), dt_end = as.Date("2019-06-04"), 
  granularity = "day")
```

The stations where measures are made are available in dataset `stations`:

```{r}
utils::head( stations )
```

Function `read_atmo()` read ATMO index and return them in a data.frame. 
The data is only containing the last year of daily historic. The air quality 
index ranges from 1 (very good) to 10 (very bad). It characterizes in a simple 
and comprehensive way the air quality of an urban agglomeration.
It is not possible to reproduce exact calculations as so2 is not available 
through the web service or with read_measures().

```{r}
utils::tail( read_atmo() )
```

Function `read_alert()` read air quality alerts issued by airparif. 

```{r}
utils::tail( read_alert() )
```

Pollutants emissions are available for 2015 as data.frame (see `emissions_epci`, `emissions_region`, `emissions_departement`):

```{r}
utils::head( emissions_epci )
```


## Installation

You can install the development version of airparis from [github](https://github.com/ardata-fr/airparis) with:

``` r
remotes::install_github("ardata-fr/airparis")
```