overviewR

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# overviewR
### Cosima Meyer
### 2020-11-27

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## What is `overviewR`?

- Small but powerful package to get a quick overview of your data
<br/>
<br/>
- Useful for academic and non-academic purposes alike
<br/>
<br/>
- Focus on plots and tables to visualize data structure
<br/>
<br/>
- Highly customizable (`tidyverse`-based) and open to suggestions <svg style="height:0.8em;top:.04em;position:relative;" viewBox="0 0 496 512"><path d="M0 256c0 137 111 248 248 248s248-111 248-248S385 8 248 8 0 119 0 256zm200-48c0 17.7-14.3 32-32 32s-32-14.3-32-32 14.3-32 32-32 32 14.3 32 32zm158.5 16.5c-14.8-13.2-46.2-13.2-61 0L288 233c-8.3 7.4-21.6.4-19.8-10.8 4-25.2 34.2-42.1 59.9-42.1S384 197 388 222.2c1.7 11.1-11.4 18.3-19.8 10.8l-9.7-8.5zM157.8 325.8C180.2 352.7 213 368 248 368s67.8-15.4 90.2-42.2c13.6-16.2 38.1 4.2 24.6 20.5C334.3 380.4 292.5 400 248 400s-86.3-19.6-114.8-53.8c-13.5-16.3 11.2-36.7 24.6-20.4z"/></svg>

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## What can you do with `overviewR`?

```r
install.packages("overviewR")
library(overviewR)
```

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## Table: `overview_tab`

```r
output_table <- overview_tab(dat = toydata, id = ccode, time = year)
```

<table class="table" style="width: auto !important; margin-left: auto; margin-right: auto;">
 <thead>
  <tr>
   <th style="text-align:left;background-color: #b7c4ce !important;"> ccode </th>
   <th style="text-align:left;background-color: #b7c4ce !important;"> time_frame </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> AGO </td>
   <td style="text-align:left;"> 1990 - 1992 </td>
  </tr>
  <tr>
   <td style="text-align:left;background-color: #b7c4ce !important;"> BEN </td>
   <td style="text-align:left;background-color: #b7c4ce !important;"> 1995 - 1999 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> FRA </td>
   <td style="text-align:left;"> 1993, 1996, 1999 </td>
  </tr>
  <tr>
   <td style="text-align:left;background-color: #b7c4ce !important;"> GBR </td>
   <td style="text-align:left;background-color: #b7c4ce !important;"> 1991, 1993, 1995, 1997, 1999 </td>
  </tr>
  <tr>
   <td style="text-align:left;"> RWA </td>
   <td style="text-align:left;"> 1990 - 1995 </td>
  </tr>
</tbody>
</table>

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## Table: `overview_crosstab`

```r
output_crosstab <- overview_crosstab(
    dat = toydata,
    cond1 = gdp,
    cond2 = population,
    threshold1 = 25000,
    threshold2 = 27000,
    id = ccode,
    time = year
  )
```

<table class="table" style="width: auto !important; margin-left: auto; margin-right: auto;">
 <thead>
  <tr>
   <th style="text-align:left;background-color: #b7c4ce !important;"> part1 </th>
   <th style="text-align:left;background-color: #b7c4ce !important;"> part2 </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> AGO (1990, 1992), FRA (1993), GBR (1997) </td>
   <td style="text-align:left;"> BEN (1996, 1999), FRA (1999), GBR (1993), RWA (1992, 1994) </td>
  </tr>
  <tr>
   <td style="text-align:left;background-color: #b7c4ce !important;"> BEN (1997), RWA (1990) </td>
   <td style="text-align:left;background-color: #b7c4ce !important;"> AGO (1991), BEN (1995, 1998), FRA (1996), GBR (1991, 1995, 1999), RWA (1991, 1993, 1995) </td>
  </tr>
</tbody>
</table>
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## Store your tables: `overview_print`

```r
overview_print(obj = output_table)
```
--

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## Store your tables: `overview_print`

```r
overview_print(
  obj = output_crosstab,
  title = "Cross table of the sample",
  crosstab = TRUE,
  cond1 = "GDP",
  cond2 = "Population"
)
```

--
<p align="center"><img src="ex3.png" width="500"></p>

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## Plots: `overview_plot`

```r
plot <- overview_plot(dat = toydata, id = ccode, time = year)
```
--
<p align="center"><img src="plot.png" width="400"></p>

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## Plots: `overview_plot`

![](plot_sample.png)
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## Plots: `overview_heat`

```r
overview_heat(toydata_red,
                ccode,
                year,
                perc = TRUE,
                exp_total = 12)
```
--

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## Plots: `overview_na`

```r
overview_na(toydata_with_na)
```
--

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## Plots: `overview_na`

```r
overview_na(toydata_with_na, 
*           perc = FALSE)
```
--

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## Store your plots

```r
library(ggplot2)

# Create plot
plot <- overview_plot(dat = toydata, id = ccode, time = year)

# Store it with ggplot
ggsave(plot, file = "plot.png")
```

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<br><br><br>
# More resources

- overviewR
  - [overviewR](https://cosimameyer.github.io/overviewR/)
  - [overviewR CheatSheet](https://github.com/cosimameyer/overviewR/blob/master/man/figures/CheatSheet_overviewR.pdf)
  - [overviewR Github repository](https://github.com/cosimameyer/overviewR)

- How to write R packages
  - [Cosima Meyer and Dennis Hammerschmidt: How to write your own R package and publish it on CRAN](https://www.mzes.uni-mannheim.de/socialsciencedatalab/article/r-package/)

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.footer[Illustrations are either created by myself, my co-author, or by canva.com]