README.Rmd

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output: github_document
---

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knitr::opts_chunk$set(
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  fig.path = "man/figures/README-",
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# brclimr

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R package to fetch zonal weather indicators for Brazilian municipalities.

## Installation

You can install the development version of brclimr like so:

``` r
remotes::install_gitlab(repo = "rdefreit/brclimr", host = "https://gitlab.inria.fr")
```

## Main functions

Currently, this package fetches zonal statistics from weather indicators created for each Brazilian municipality with data from the BR-DWGD project (Xavier et al. 2022). For each municipality and weather indicator, a series of daily zonal statistics was calculated considering the data cells that intersects the municipality, like mean, max, min, sd and sum.

For the BR-DWGD project, the following data can be retrieved with this package

```{r}
library(brclimr)

product_info(product = "brdwgd")
```

To fetch data for a specific product, indicator and statistic, use the fetch_data function. For example, lets consider the Rio de Janeiro, RJ municipality (IBGE code number 3304557), data product "brdwgd", average relative humidity, from 2010-10-15 to 2010-10-20.

```{r}
fetch_data(
    code_muni = 3304557,
    product = "brdwgd",
    indicator = "rh",
    statistics = "mean",
    date_start = as.Date("2010-10-15"),
    date_end = as.Date("2010-10-20")
  )
```

## Another example

```{r}
tmax <- fetch_data(
  code_muni = 3303401,
  product = "brdwgd",
  indicator = "tmax",
  statistics = "mean",
  date_start = as.Date("2010-01-01"),
  date_end = as.Date("2012-01-01")
)

tmin <- fetch_data(
  code_muni = 3303401,
  product = "brdwgd",
  indicator = "tmin",
  statistics = "mean",
  date_start = as.Date("2010-01-01"),
  date_end = as.Date("2012-01-01")
)

pr <- fetch_data(
  code_muni = 3303401,
  product = "brdwgd",
  indicator = "pr",
  statistics = "sum",
  date_start = as.Date("2010-01-01"),
  date_end = as.Date("2012-01-01")
)

tmax$name <- "Tmax_avg"
tmin$name <- "Tmin_avg"
```

```{r}
library(ggplot2)

ggplot(data = rbind(tmax, tmin), aes(x = date, y = value, color = name)) +
  geom_line() +
  scale_x_date(date_breaks = "2 months", date_labels =  "%m/%y") +
  ylim(0, NA) +
  labs(
    title = "Nova Friburgo, RJ",
    x = "Date", 
    y = "Temperature (average)",
    color = ""
  ) +
  theme_bw() +
  theme(legend.position = "bottom", legend.direction = "horizontal")
```

```{r}
ggplot(data = pr, aes(x = date, y = value)) +
  geom_line(color = "blue") +
  scale_x_date(date_breaks = "2 months", date_labels =  "%m/%y") +
  ylim(0, NA) +
  labs(
    title = "Nova Friburgo, RJ",
    x = "Date", 
    y = "Precipitation (sum)",
    color = ""
  ) +
  theme_bw() +
  theme(legend.position = "bottom", legend.direction = "horizontal")
```