This is a quick tutorial on using the most useful functions in the `lares`

library for quick data analysis: `freqs`

, `distr`

, and `corr_var`

. With these you can explore and understand the interaction between all or specific variables within a dataset.

First, we load the `lares`

and `tidyverse`

libraries (for `dplyr`

and `ggplot2`

)

```
library(lares) # devtools::install_github("laresbernardo/lares")
library(tidyverse)
```

Then, we load the `dft`

dataset within the `lares`

library. It is a useful subset from the Titanic survival dataset.

`data(dft)`

Letâ€™s quickly see its structure:

`df_str(dft, return = "plot")`

`head(dft, 5)`

This function lets us group, count, calculate percentages and cumulatives for further transformations or for visual analysis. For more details: `?freqs`

```
# How many survived?
dft %>% freqs(Survived)
```

```
# How many survived and see plot?
dft %>% freqs(Survived, plot = T, results = F)
```

```
# How many survived per class?
dft %>% freqs(Survived, Pclass, plot = T, results = F)
```