# sampledatasets: A collection of Sample DataSets

    library(sampledatasets)

    library(ggplot2)

    library(dplyr)
    #>
    #> Adjuntando el paquete: 'dplyr'
    #> The following objects are masked from 'package:stats':
    #>
    #>     filter, lag
    #> The following objects are masked from 'package:base':
    #>
    #>     intersect, setdiff, setequal, union

# 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

    # 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

    # 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.