Rmd_notebook1.Rmd

---
title: 'Notebook: htmwlwidgets'
output:
  html_notebook: default
  html_document: default
---

## dygraphs

https://github.com/rstudio/dygraphs

Dygraphs provides rich facilities for charting time-series data in R and includes support for many interactive features including series/point highlighting, zooming, and panning.

```{r}
library(dygraphs)
dygraph(nhtemp, main = "New Haven Temperatures") %>% 
  dyRangeSelector(dateWindow = c("1920-01-01", "1960-01-01"))
```

## Leaflet

http://rstudio.github.io/leaflet/

Leaflet is a JavaScript library for creating dynamic maps that support panning and zooming along with various annotations like markers, polygons, and popups.

```{r, message=FALSE, warning=FALSE}
library(leaflet)
cities <- read.csv("cities.csv")
leaflet(cities) %>% addTiles() %>%
  addCircles(lng = ~Long, lat = ~Lat, weight = 1,
    radius = ~sqrt(Pop) * 30, popup = ~City
  )
```

Rmd_notebook_bash_python.Rmd

---
title: "Python and R with Feather"
output: html_notebook
---

```{r setup, include=FALSE}
library(feather)
library(ggplot2)
setwd('~/sol-eng-sales/vignettes/notebooks/demos/5-feather')
```


First use bash to append together several data files into a single file we can read and manipulate:

```{bash}
cat flights1.csv flights2.csv flights3.csv > flights.csv
```

Now use **pandas** to read and filter the data. We'll pass it to R using the high-performance [feather](https://blog.rstudio.org/2016/03/29/feather/) serialization format:

```{python}
import pandas
import feather

# Read flights data and select flights to O'Hare
flights = pandas.read_csv("flights.csv")
flights = flights[flights['dest'] == "ORD"]

# Select carrier and delay columns and drop rows with missing values
flights = flights[['carrier', 'dep_delay', 'arr_delay']]
flights = flights.dropna()
print flights.head(10)

# Write to feather file for reading from R
feather.write_dataframe(flights, "flights.feather")
```

Now read from *flights.feather* into an R data frame and plot arrival delays by carrier using **ggplot2**:

```{r}
library(feather)
library(ggplot2)

# Read from feather and plot
flights <- read_feather("flights.feather")
ggplot(flights, aes(carrier, arr_delay)) + geom_boxplot()
```