---
title: "CENSOAGRO"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{CENSOAGRO}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```


## Overview

The Census of Agriculture (Censo Agropecuário) is Brazil's comprehensive survey of agricultural establishments and activities, conducted by IBGE (Instituto Brasileiro de Geografia e Estatística). This census collects detailed information about:

- **Agricultural establishments**: characteristics, size, and management
- **Agricultural producers**: demographics, education, and land ownership conditions
- **Production activities**: crops, livestock, and agroindustry operations
- **Rural employment and labor**: workforce characteristics and wages
- **Agricultural inputs**: machinery, equipment, and technology adoption

The census provides critical data for agricultural policy, market research, and understanding the structure of Brazilian agriculture across regional and temporal dimensions.

### Data Coverage

Data is collected at multiple geographic levels:
- **Country level**: aggregate national statistics
- **State level**: disaggregated by Brazilian states
- **Municipality level**: available for select datasets (currently `"livestock_production"`)

Historical data spans from 1920 onwards, with different time series available for different datasets based on IBGE's survey methodology evolution.

***

## Available Datasets

### 1. **agricultural_land_area**
Provides comprehensive data on total agricultural land area and the number of agricultural properties.

- **Key metrics**: Total land area (hectares), number of properties
- **Time period**: 1920, 1940, 1950, 1960, 1970, 1975, 1980, 1985, 1995, 2006, 2017
- **Geographic levels**: Country, State
- **Use case**: Track long-term trends in farm consolidation and total agricultural land expansion

### 2. **agricultural_area_use**
Details how agricultural properties use their land (crop farming, pasture, forests, etc.).

- **Key metrics**: Area by use category (temporary crops, permanent crops, natural pastures, planted pastures, forest for forest production, protected natural vegetation, other areas)
- **Time period**: 1970 onwards (1970, 1975, 1980, 1985, 1995, 2006, 2017)
- **Geographic levels**: Country, State
- **Use case**: Analyze land use transitions, deforestation patterns, and agricultural intensification

### 3. **agricultural_employees_tractors**
Captures information about the agricultural workforce and mechanization levels.

- **Key metrics**: Number of employees, number of tractors, employed persons
- **Time period**: 1970 onwards (1970, 1975, 1980, 1985, 1995, 2006, 2017)
- **Geographic levels**: Country, State
- **Use case**: Study agricultural mechanization trends and rural employment dynamics

### 4. **agricultural_producer_condition**
Describes the tenure status of agricultural land (ownership, rental, partnership, etc.).

- **Key metrics**: Number of properties by producer condition (owner, tenant, partner, occupant)
- **Time period**: 1920, 1940, 1950, 1960, 1970, 1975, 1980, 1985, 1995, 2006, 2017
- **Geographic levels**: Country, State
- **Use case**: Understand land tenure structures and changes in property ownership patterns

### 5. **animal_production**
Details the number of livestock animals farmed by species and type.

- **Key metrics**: Number of animals by species (cattle, pigs, poultry, sheep, horses, goats, water buffalo, etc.), number of establishments
- **Time period**: 1970 onwards (1970, 1975, 1980, 1985, 1995, 2006, 2017)
- **Geographic levels**: Country, State
- **Use case**: Monitor livestock herd sizes and sectoral changes in animal agriculture

### 6. **animal_products**
Quantifies production volumes of animal-based products.

- **Key metrics**: Production quantities (eggs, milk, honey, wool, hide, etc.)
- **Time period**: 1920, 1940, 1950, 1960, 1970, 1975, 1980, 1985, 1995, 2006, 2017
- **Geographic levels**: Country, State
- **Use case**: Track historical trends in dairy, poultry, and other animal product sectors

### 7. **vegetable_production_area**
Provides detailed crop production data including area planted and volume produced.

- **Key metrics**: Area planted (hectares), quantity produced (kilograms), number of establishments by crop type
- **Time period**: 1920, 1940, 1950, 1960, 1970, 1975, 1980, 1985, 1995, 2006, 2017
- **Geographic levels**: Country, State
- **Use case**: Comprehensive analysis of crop production patterns and agricultural productivity

### 8. **vegetable_production_temporary**
Focuses specifically on temporary crops (annual crops that must be replanted each season).

- **Key metrics**: Area planted, quantity produced for crops like soybeans, corn, beans, cassava
- **Time period**: 1970 onwards (1970, 1975, 1980, 1985, 1995, 2006, 2017)
- **Geographic levels**: Country, State
- **Use case**: Study annual crop production cycles and seasonal variations

### 9. **vegetable_production_permanent**
Focuses on permanent crops (perennial crops that produce for multiple years).

- **Key metrics**: Area planted, quantity produced for crops like coffee, sugarcane, cocoa, oranges
- **Time period**: 1940 onwards (1940, 1950, 1960, 1970, 1975, 1980, 1985, 1995, 2006, 2017)
- **Geographic levels**: Country, State
- **Use case**: Analyze long-cycle crop production and regional specialization

### 10. **livestock_production**
Specialized dataset on bovine cattle production and related establishments.

- **Key metrics**: Number of cattle establishments, herd size, number of properties
- **Time period**: 2017 (most recent census year)
- **Geographic levels**: Country, State, **Municipality** (unique to this dataset)
- **Use case**: Detailed regional analysis of cattle ranching, including municipality-level data

***

## Function Parameters

### 1. **dataset**
Selects which dataset to download. See dataset descriptions above.

```r
dataset = "agricultural_land_area"  # character string
```

### 2. **raw_data**
Controls whether to download the original data or the processed/cleaned version.

- `TRUE`: Returns raw data exactly as published by IBGE
- `FALSE`: Returns treated data with standardized formatting, variable names in English, and consistent units

**Default behavior**: Raw data typically requires more cleaning and interpretation, while treated data is ready for immediate analysis.

```r
raw_data = FALSE  # logical
```

### 3. **geo_level**
Specifies the geographic aggregation level.

- `"country"`: National aggregate
- `"state"`: Disaggregated by Brazilian state
- `"municipality"`: Available only for `"livestock_production"` dataset

```r
geo_level = "state"  # character string
```

### 4. **time_period**
Defines which year(s) to download. Availability varies by dataset:

| Dataset | Available Years |
|---------|-----------------|
| `agricultural_land_area` | `1920, 1940, 1950, 1960, 1970, 1975, 1980, 1985, 1995, 2006, 2017` |
| `agricultural_area_use` | `1970, 1975, 1980, 1985, 1995, 2006, 2017` |
| `agricultural_employees_tractors` | `1970, 1975, 1980, 1985, 1995, 2006, 2017` |
| `agricultural_producer_condition` | `1920, 1940, 1950, 1960, 1970, 1975, 1980, 1985, 1995, 2006, 2017` |
| `animal_production` | `1970, 1975, 1980, 1985, 1995, 2006, 2017` |
| `animal_products` | `1920, 1940, 1950, 1960, 1970, 1975, 1980, 1985, 1995, 2006, 2017` |
| `vegetable_production_area` | `1920, 1940, 1950, 1960, 1970, 1975, 1980, 1985, 1995, 2006, 2017` |
| `vegetable_production_temporary` | `1970, 1975, 1980, 1985, 1995, 2006, 2017` |
| `vegetable_production_permanent` | `1940, 1950, 1960, 1970, 1975, 1980, 1985, 1995, 2006, 2017` |
| `livestock_production` | `2017` |

You can request a single year or a range of years:

```r
time_period = 2006           # single year
time_period = c(1995, 2006)  # multiple specific years
time_period = 1995:2006      # will select years within this range that are available
```

### 5. **language**
Output language for variable names and labels.

- `"pt"`: Portuguese
- `"eng"`: English

```r
language = "eng"  # character string
```

***

## Examples

```{r eval=FALSE}
# download treated land area data at the country level in 2017
data <- load_censoagro(
  dataset = "agricultural_land_area",
  raw_data = FALSE,
  geo_level = "country",
  time_period = 2017,
  language = "eng"
)

# download treated temporary crop data by state in 1995 in portuguese
data <- load_censoagro(
  dataset = "vegetable_production_temporary",
  raw_data = FALSE,
  geo_level = "state",
  time_period = 1995,
  language = "pt"
)

# download municipality-level cattle data (only available for livestock_production)
data <- load_censoagro(
  dataset = "livestock_production",
  raw_data = FALSE,
  geo_level = "municipality",
  time_period = 2017,
  language = "eng"
)
```

## Data Notes

### Raw vs. Treated Data

- **Raw data** (`raw_data = TRUE`): Exactly as published by IBGE, with original formatting and Portuguese variable names
- **Treated data** (`raw_data = FALSE`): Cleaned and standardized with English variable names, consistent units (hectares for area, kilograms for production quantities), and NA values properly handled

### Data Organization

When using treated data, the output is typically in long format with one row per observation unit, containing:
- Geographic identifiers (state, municipality if applicable)
- Year of the census
- Product/category names (crop type, animal species, etc.)
- Quantitative measurements (area, quantity, count)
- Number of establishments/properties

### Important Considerations

1. **Time gaps**: Census data is not collected every year. Years with no data simply won't be available.
2. **Geographic changes**: Brazil's state boundaries have changed historically; use caution when comparing very old data
3. **Definition changes**: IBGE's classification of crops and agricultural activities has evolved. Variables may not be directly comparable across all decades.
4. **Municipality data**: Currently only available for `livestock_production` in 2017
5. **Download size**: Historical data requests with multiple years may be large; plan accordingly

### Citing the Data

When using this data in research or publications, cite:

> IBGE - Instituto Brasileiro de Geografia e Estatística. Censo Agropecuário. Available at: https://sidra.ibge.gov.br/pesquisa/censo-agropecuario

***
