---
title: "ANLY 512 - Lab 1"
output: 
  flexdashboard::flex_dashboard:
    Name: "Chirag Shetty"
    orientation: columns
    vertical_layout: fill
    social: menu
    source: embed
    html_document:
    df_print: paged
    pdf_document: default
---


### Financial Indicators
```{r}
library(quantmod)
library(plyr)
library(DT)
library(xts)
library(dygraphs)
what_metrics <- yahooQF(c("Price/Sales",
 "P/E Ratio",
 "Price/EPS Estimate Next Year",
 "PEG Ratio",
 "Dividend Yield",
 "Market Capitalization"))
tickers<-c("AAPL","MSI","MSFT","TSLA")
metrics <- getQuote(paste(tickers, sep="", collapse=";"), what=what_metrics)
#Add tickers as the first column and remove the first column which had datestamps
metrics <- data.frame(Symbol=tickers, metrics[,2:length(metrics)])
#Change colnames
colnames(metrics) <- c("Symbol", "P-E Ratio", "Price EPS Estimate Next Year",
"Div Yield", "Market Cap")
#Persist this to the csv file
#write.csv(metrics, "FinancialMetrics.csv", row.names=FALSE)
DT::datatable(metrics)
```
Sidebar {.sidebar}



#Insights
The data selected was Apple, Msft, TSLA and MSI. We see that the faster earning potential was of TSLA with a steep rise. MSI falls out because of its market cap being significantly lower than the other 3 companies. 

Also, we see TSLA's stock price going lower than the other 3 companies. This says that TSLA can have a higher growth potential and a short term gain. 

### Apple Stock Price
```{r}
library(xts)
library(dygraphs)
AAPL <- getSymbols('AAPL', auto.assign = FALSE, from = "2018-04-01")
dygraph(AAPL[, 1:4]) %>%
 dyAxis("y", label="Price") %>%
 dyCandlestick()
```
### Motorola Stock Price
```{r}
library(xts)
library(dygraphs)
Motorola <- getSymbols('MSI', auto.assign = FALSE, from = "2018-04-01")
dygraph(Motorola[, 1:4]) %>%
 dyAxis("y", label="Price") %>%
 dyCandlestick()
```
### Microsoft Stock Price
```{r}
library(xts)
library(dygraphs)
MSFT <- getSymbols('MSFT', auto.assign = FALSE, from = "2018-04-01")
dygraph(MSFT[, 1:4]) %>%
 dyAxis("y", label="Price") %>%
 dyCandlestick()
```
### TSLA Stock Price

```{r}
library(xts)
library(dygraphs)
TSLA <- getSymbols('TSLA', auto.assign = FALSE, from = "2018-04-01")
dygraph(TSLA[, 1:4]) %>%
dyAxis("y", label="Price") %>%
dyCandlestick()
```

Sidebar {.sidebar}-----------------------------------------------------------------------
#Insights
The data selected was Apple, Msft, TSLA and MSI. We see that the faster earning potential was of TSLA with a steep rise. MSI falls out because of its market cap being significantly lower than the other 3 companies. 

Also, we see TSLA's stock price going lower than the other 3 companies. This says that TSLA can have a higher growth potential and a short term gain. 
Row {.tabset .tabset-fade}-----------------------------------------------------------------------