---
title: "sampledatasets: A collection of Sample DataSets"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{sampledatasets: A collection of Sample DataSets}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

```{r setup}
library(sampledatasets)

library(ggplot2)

library(dplyr)

```

# Introduction

The `sampledatasets` package provides a diverse collection of sample datasets, covering various fields such as automotive performance and safety, historical demographics, socioeconomic indicators, and recreational data. **This package serves as a valuable resource for researchers and analysts seeking to perform analyses and derive insights from classic datasets in R**.

## Dataset Suffixes

Each dataset includes a suffix indicating its format to help users identify the data type easily. The suffixes include:

`df`: A standard data frame.
`tbl`: A tibble data frame.

### Example Datasets

The `sampledatasets` package includes the following datasets:

- mtcars_df: A data frame containing motor trend car data, including miles per gallon, horsepower, and weight.

- swiss_df: A data frame of Swiss socioeconomic data, including fertility rates and education levels.

- cars_df: A data frame of car speed and stopping distances.
arbuthnot_tbl: A tibble of historical birth records by year, including counts of boys and girls.

- cards_tbl: A tibble representing a standard 52-card deck, including values, suits, and colors.

All datasets in sampledatasets retain their original structure and content, ensuring integrity and reliability for analyses.

## Visualizing Data with ggplot2

To demonstrate the datasets, here are a few visualization examples using the ggplot2 package.

1. Visualization of Miles Per Gallon in Cars

```{r ggplot2}

# Example: Scatter plot of miles per gallon vs weight
mtcars_df %>%
  ggplot(aes(x = wt, y = mpg, color = cyl)) +
  geom_point(alpha = 0.7) +
  labs(
    title = "Miles Per Gallon vs Weight",
    x = "Weight (1000 lbs)",
    y = "Miles per Gallon",
    color = "Cylinders"
  ) +
  theme_minimal()


```


2. Distribution of Fertility Rates in Swiss Data

```{r ggplot2_001}

# Example: Histogram of fertility rates
swiss_df %>%
  ggplot(aes(x = Fertility)) +
  geom_histogram(binwidth = 5, fill = "blue", color = "black", alpha = 0.7) +
  labs(
    title = "Distribution of Fertility Rates in Switzerland",
    x = "Fertility Rate",
    y = "Count"
  ) +
  theme_minimal()


```


## Conclusion

The `sampledatasets` package provides an extensive collection of datasets that are useful for a wide range of analyses. The suffixes in dataset names make it easy to identify the type of data, ensuring an efficient analysis process.

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