ramnathv

• 0.1. References
• 0.2. Other cheatsheets
• 0.3. Manage multiple gcloud config configurations
  • 0.3.1. Switch gcloud context with gcloud config
• 0.4. Credentials
• 0.5. info
• 0.6. projects
• 0.7. zones & regions
• 0.8. Organization
• 0.9. billing

ramnathv

---
title: New York City Taxi & Limousine Commission (TLC) Trip Data Analysis Using Sparklyr
  and Google BigQuery
author: "Mirai Solutions"
date: 8\textsuperscript{th} January 2018
output:
  html_document:
    theme: flatly
params:
  # gcp_json_keyfile: gcp_keyfile.json

ramnathv

This is a proof-of-concept of a parser to convert a markdown file to a ctv file, that is required for task views. The basic idea is to use a combination of YAML and markdown sections in the md file, parse it and convert it into a payload, and render it using a template as specified by the ctv package.

Structure of Markdown File

---
name: Working with data on the web
maintainer: Scott Chamberlain, Karthik Ram, Christopher Gandrud
email: scott at ropensci.org
version: 2013-09-17

ramnathv

---
title       : RevealJS with Bootstrap
framework   : revealjs
widgets     : [bootstrap]            # {mathjax, quiz, bootstrap}
---

## Read-And-Delete

1. Edit YAML front matter
2. Write using R Markdown

ramnathv

App Install Plan

Critical

• iTerm2

  • https://iterm2.com/

• Command Line Tools

  • xcode-select –install

ramnathv

This is a demo of how to get plotly events back to shiny server.

Let us start by loading required libraries and preparing data. We use the ubiquitous mtcars dataset.

# Load Libraries ----
library(plotly)
library(shiny)
library(htmlwidgets)

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library(WDI)
top10 = c('US', 'CN', 'JP', 'DE', 'FR', 'GB', 'BR', 'RU', 'IT', 'IN')
gdp = WDI(top10, indicator = "NY.GDP.MKTP.CD", start = 1980, end = 2012)
gdp = transform(gdp, NY.GDP.MKTP.CD = NY.GDP.MKTP.CD/10^9)

library(rCharts)
n1 <- nPlot(NY.GDP.MKTP.CD ~ year, data = gdp, group = 'country',
  type = 'stackedAreaChart', width = 800, height = 400
)
n1$yAxis(

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example.md: example.Rmd
	./knit

example.ipynb: example.md
	notedown example.md | sed 's/%%r/%%R/' > example.ipynb

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""" Implementation of OKapi BM25 with sklearn's TfidfVectorizer
Distributed as CC-0 (https://creativecommons.org/publicdomain/zero/1.0/)
"""

import numpy as np
from sklearn.feature_extraction.text import TfidfVectorizer
from scipy import sparse


class BM25(object):

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library(ggplot2)
library(datasauRus)
library(gganimate)

p <- ggplot(datasaurus_dozen, aes(x = x, y = y, frame = dataset)) +
  geom_point() +
  theme(legend.position = "none")

gganimate(p, title_frame = FALSE)