data-607-tidyverse-TNS.Rmd

---
title: "DATA-607 TIDYVERSE ASSIGNMENT"
author: "Tage N Singh"
date: "`r Sys.Date()`"
output:
  prettydoc::html_pretty:
    theme: cayman
    highlight: vignette
vignette: >
  %\VignetteIndexEntry{Vignette Title}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

This vignette will provide a brief exploration of the "tidyverse" package using its built-in libraries
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The tidyverse is a powerful collection of R packages that are actually data tools  All packages of the tidyverse share an underlying  common APIs as listed below. 
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Lists

- ggplot2, which implements the grammar of graphics. You can use it to visualize your data.
- dplyr is a grammar of data manipulation. You can use it to solve the most common data manipulation challenges.
- tidyr helps you to create tidy data or data where each variable is in a column, each observation is a row end each value is a cell.
- readr is a fast and friendly way to read rectangular data.
- purrr enhances R’s functional programming (FP) toolkit by providing a complete and consistent set of tools for working with functions and vectors.
- tibble is a modern re-imaginging of the data frame.
- stringr provides a cohesive set of functions designed to make working with strings as easy as posssible
-  forcats provide a suite of useful tools that solve common problems with factors.

Now for the package
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```{r setup}
#Loading just the "tidyverse" library !

library(tidyverse)

```

```{r tidyverse usage-1}

# For this exercise we are using a dataset from kaggle.com which contain 
#information about avacado sales in various cities in the USA

# ---------- Using the "rear" function "read_csv" -------

avacado <- data.frame(read_csv(file = "https://raw.githubusercontent.com/tagensingh/SPS-DATA607-TIDYVERSE/main/avocado.csv"))

# ---------- Using the "tibble" function to look at a snapshot of the dataframe -------

tibble(avacado)

```

```{r tidyverse usage-2}

# ---------- Using the "arrange" function  from "dplyr"to sort the dataframe by date-------

avacado_date <- arrange(avacado,Date)

tibble(avacado_date)


# ---------- Using the "ggplot" function  from "ggplot2"to chart the pricing density of avacados-------

# Histogram overlaid with kernel density curve
ggplot(avacado, aes(x=AveragePrice)) + 
    geom_histogram(aes(y=..density..),      # Histogram with density instead of count on y-axis
                   binwidth=.1,
                   colour="black", fill="white") +
    geom_density(alpha=.1, fill="#FF6666")+# Overlay with transparent density plot
    ggtitle("Avacados Pricing Density")
```

As is shown above, the tidyverse packages is one of the most versatile packages in the R sphere....

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