---
title: "Final Project"
author: "Gayathri Mutyala"
output:
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    source_code: embed
---

```{r setup, include=FALSE}

knitr::opts_chunk$set(echo = FALSE)


```


```{r, echo = FALSE, message = FALSE}

library(readr)
mydata<-read_csv("C:/Users/gmutya048/Downloads/Discover-2018-YearEndSummary.csv")
#View(mydata)
     
```

Overview
===================================== 


##Introduction

For this Quantified self Final project I have choosen to Analyze my credit card data. So
As a part of the project I gatherd my data from one on my ards.I have dumped all my trascations from my Discover credit card account into a CSV file. Insted of looking at all the transaction I have choosen only transactions that I made in the year of 2018. All the transactions from January to December in the year of 2018.I cleaned the data further to create this dash borad.
 


### Data variables
- Trans_Date = Exact date on which transaction occured
- Post_Date = Exact date the transaction was posted
- Month = Month of transaction
- Description = Information about my Transaction and merchant details
- Amount = The tarnsaction amount
- Category = Which type of transcation it was based on the decription. 



### My five questions
1. What are my spending categories and in which category I spent more?
2. Which month has Highest spending?
3. Which Month is having highest Payments?
4. How often I visited Whole foods?
5. What is the highest amount I spent at Whole foods?



Highest Spending Categories
====================================

### My Spending Catgories


```{r, echo = FALSE, message = FALSE}

library(ggplot2)
category <- ggplot(mydata, aes(x=Category, y=Amount, fill=Category)) + 
  geom_bar(stat = "identity", fill = "LightBlue")+
  labs(title = "Transactions by Category", x = "Category", y = "Amount") +
  coord_flip()

category


```


Monthly Spending
====================================



### Maximum Spendings and Payments in Each Month


```{r, echo = FALSE, message = FALSE}



library(ggplot2)
month <- ggplot(mydata, aes(x=Month, y=Amount)) +   
  geom_bar(aes(fill = Category),  stat="identity") +
  labs(title = "Spend by Month and Category", x = "Month", y = "Amount") +
  theme(legend.position = "Right") +
  scale_fill_discrete(name="Category") +
  theme(legend.position = "right")

month

```




Spendings at Super Markets
====================================

###My total spendings at Whole Foods


```{r, echo = FALSE, message = FALSE}

library(plotly)
Wholefoods <- ggplot(mydata[mydata$Description=='WHOLEFDS DEV 10053 WAYNE PA',], aes(x=Post_Date, y=Amount, Post_Date=Post_Date)) +
  geom_point(aes(col=Amount, size=Amount)) +
  labs(title = "How Often I shop at Whole foods", x = "Date", y = "Amount")

#(gglyft <- ggplotly(Wholefoods, tooltip = c("Post_Date", "y")))

Wholefoods

```

Conclusion/Quesitions Addressed
====================================

###Observations


1. My Highest spendings are in merchantise category which means I need to watch out my spending on Shopping cloths and other merchantise items.

2. My top categories of spendings are Merchendise, Supermarket, Restaurant, Travel/Entertainment and Services.

3. I spent least on Supermarets and more on Restaurants. I should start eating home more often. 

4. I visit Whole foods at least once in a month. My highest spending in Whole foods is 94$ where as my lowest spending is 13$.

5. I spent more in the month of March and especially more on merchendise.

6. I also have good payments in my account which shows that I am good at clearing my cards often.