README.Rmd

---
output: github_document
---


```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "80%"
)
```



## The `esaps` package <img src="man/figures/logo.png" style="margin-left:10px;margin-bottom:5px;" width="160" align="right"></a>

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### Description

It allows structuring electoral data of different size and structure to calculate various indicators frequently used in the studies of electoral systems and party systems. Indicators of electoral volatility, electoral disproportionality, party nationalization and the effective number of parties are included.

### Installation

```{r eval=FALSE}
# Install speech from CRAN
install.packages("esaps")

# The development version from GitHub:
if (!require("remotes")) install.packages("remotes")
remotes::install_github("Nicolas-Schmidt/esaps")
```



### Functions


| Indicator                     | Method                                        | Variables                                       | Function                  |
| -----------------------------| ------------------------------                        | ---------------   |-------------------------- |
| Electoral Volatility          | [Pedersen (1979)](http://bit.ly/2p4cyZQ)             | `election` `unit` `party` `votes`               | `evolat(., method=1)` |
|                               | [Powell and Tucker (2014)](http://bit.ly/2FpoeBm)    | `election` `unit` `party` `votes`               | `evolat(., method=2)` |
|                               | [Torcal and Lago (2015)](http://bit.ly/2FD83zE)      | `election` `unit` `party` `votes` `M`           | `evolat(., method=3)` |
| Effective Number of Parties   | [Laakso and Taagepera (1979)](http://bit.ly/2oYU4dV) | `election` `unit` `party` `votes` or `seats`    | `enp()`                   |
| Party System Nationalization  | [Mainwaring and Jones (2003)](https://bit.ly/2w9QgtO)| `election` `unit` `party` `votes` `votes_nac`   | `psns(., method=1)`    |
|                               | [Chhibber and Kollman (2004)](https://bit.ly/2oj76SY)| `election` `unit` `party` `votes` `votes_nac`   | `psns(., method=2)`    |
| Party Nationalization         | [Mainwaring and Jones (2003)](https://bit.ly/2w9QgtO)| `election` `unit` `party` `votes`               | `psns(., method=1,pn=TRUE)`|
| Electoral Disproportionality  | Rae (1971)                                           | `election` `unit` `party` `votes` `seats`       | `dispro(., method=1)` |
|                               | [Loosemore and Hanby (1971)](https://bit.ly/2B1mIDH) | `election` `unit` `party` `votes` `seats`       | `dispro(., method=2)` |
|                               | Lijphart_1 (1986)                                    | `election` `unit` `party` `votes` `seats`       | `dispro(., method=3)` |
|                               | [Lijphart_2 (1994)](https://bit.ly/2McLshB)          | `election` `unit` `party` `votes` `seats`       | `dispro(., method=4)` |
|                               | [Gallagher (1991)](https://bit.ly/2M6CPoy)           | `election` `unit` `party` `votes` `seats`       | `dispro(., method=5)` |
|                               | [Cox and Shugart (1991)](https://bit.ly/2M9Bttr)     | `election` `unit` `party` `votes` `seats`       | `dispro(., method=6)` |



### Indicators and Variables

<img src="man/figures/net.png" style="margin-center:30px;margin-bottom:5px;" width="1160" align="center"></a>



### Examples

#### Load data
```{r}
library(esaps)

votes <- list(data.frame(country = rep("ARG", 3),
                         year = c(1995, 2000, 2005),
                         party_A = c(40,10,20),
                         party_B = c(35,20,40),
                         party_C = c(25,70,40)),
              data.frame(country = rep("URY", 4),
                         year = c(1995, 2000, 2005, 2010),
                         party_A = c(30,30,20,20),
                         party_B = c(30,50,40, 30),
                         party_C = c(30,10,30, 25),
                         party_D = c(10,10,10,25)),
              data.frame(country = rep("BRA", 2),
                         year = c(1993, 1998),
                         party_A = c(30, 55),
                         party_B = c(70, 45)))

votes

votes <- convert_esaps(dataset = votes, unit.name = "country", election.name = "year")

votes

## VOTES AND SEATS

votes_2 <- data.frame(
        year = c(2000, 2005), 
        country = "URY", 
        votes_party1 = c(20, 30), 
        votes_party2 = c(30, 35),
        votes_party3 = c(40, 25),
        votes_party4 = c(10, 10), 
        seats_party1 = c(25, 35),
        seats_party2 = c(20, 30),
        seats_party3 = c(40, 30),   
        seats_party4 = c(15, 5)   
)

votes_2

votes_2c <- convert_esaps(dataset = votes_2, unit.name = "country", election.name = "year", seats = TRUE)

votes_2c


```

#### Functions
Electoral volatility 
```{r}
evolat(votes, 1)

evolat(tidy_data = votes, method = 1, summary = TRUE)
```

Effective Number of Parties
```{r}
enp(votes)

```

Electoral Disproportionality
```{r}

votes_2

v2 <- convert_esaps(dataset = votes_2, unit.name = "country", election.name = "year", seats = TRUE)
dispro(v2, 1:6, 1)

library(magrittr)

convert_esaps(dataset = votes_2, unit.name = "country", election.name = "year", seats = TRUE) %>%
        dispro(1:3)


dispro(tidy_data = v2, method = c("Rae", "Gallagher"))

```

Party System Nationalization Score and Party Nationalization Score
```{r}
votes3 <- data.frame(election = rep(2000,4),
                    unit  = rep(c("District_1", "District_2"), each = 2),
                    party = rep(c("party_A", "party_B"), 2),
                    votes = c(0.60,0.40, 0.30, 0.70),
                    votes_nac = rep(c(0.55,0.45),2)
                    )

votes3

psns(tidy_data = votes3, method = 1)

psns(tidy_data = votes3, method = 1, pns = TRUE)


```


Electoral volatility in Uruguay

```{r, message=FALSE, fig.width = 6, fig.height = 3}
library(Boreluy) # https://nicolas-schmidt.github.io/Boreluy/
library(tidyverse)

map_df(c(1984, 1989, 1994, 1999, 2004), nacional_uy) %>% 
    as_esaps() %>% 
    evolat("Pedersen") %>% 
        ggplot(aes(x = election, y = eVolat)) +
        geom_line(aes(group = 1)) + 
        geom_point(size = 2, color = "red") +
        theme_minimal()
```



Linear Model
```{r f1, message = FALSE, fig.width = 6, fig.height = 3, warning=FALSE}
library(tidyverse)

dat <- inner_join(evolat(votes, 1), enp(votes))

dat

lm(formula(dat[,4:3]), data = dat)

ggplot(dat, aes(x = enp, y = eVolat )) +
    geom_point() + 
    geom_smooth(method = lm, se = TRUE) +
    theme_minimal()


```


### Citation

To cite `esaps` in publications, please use:

```{r eval=FALSE}
citation("esaps")
```

### Author

Nicolas Schmidt (<nschmidt@cienciassociales.edu.uy>)