Install the newest version of R. Additionally, I highly recommend R-Studio for working with R regularly (but the basic command line will work just fine for most applications). Once R is installed, you can install GTK directly from within R (details below). In short:
RGtk2 package by running: install.packages("RGtk2", depen=T)
| library(httr) | |
| library(devtools) | |
| # make httr set CURL to ignore SSL verification problems | |
| # (needed if the SSL proxy replaces certs with its own) | |
| set_config(config(ssl.verifypeer = 0L)) | |
| # set proxy details | |
| set_config(use_proxy("10.10.10.10",8080)) |
| library(magrittr) | |
| library(dplyr) | |
| sales <- data_frame("cust_id" = sample(1000:1999, replace = T, size = 10000), | |
| "sales_value" = abs(round(rnorm(10000, 28, 13))), | |
| "date" = as.Date("2012/1/1") + 700 * sort(stats::runif(10000))) | |
| # sales_value: 產生均值為28，方差為13的1萬個數，用來模擬用戶的消費情況 | |
| # cust_id: 從1000到1999這些數字中，# 有放回抽樣進行取樣， | |
| # 一共取1萬筆消費記錄，平均每個樣本取10次 | |
| # date: 產生1萬個服從0,1上均勻分佈的數 |
| # https://datawarrior.wordpress.com/2015/08/12/codienerd-1-r-or-python-on-text-mining/ | |
| # import all necessary libraries | |
| from nltk.stem import PorterStemmer | |
| from nltk.tokenize import SpaceTokenizer | |
| from nltk.corpus import stopwords | |
| from functools import partial | |
| from gensim import corpora | |
| from gensim.models import TfidfModel | |
| import re |
| # Installing TOR on mac: brew install tor | |
| # Run TOR on custom port: tor --SOCKSPort 9050 | |
| # Check the 'origin' field in the response to verify TOR is working. | |
| library(httr) | |
| GET("https://httpbin.org/get", use_proxy("socks5://localhost:9050")) | |
| # Set proxy in curl | |
| library(curl) | |
| h <- new_handle(proxy = "socks5://localhost:9050") |
The Leaflet JS mapping library has lots of plugins available. The Leaflet package for R provides direct support for some, but far from all, of these plugins, by providing R functions for invoking the plugins.
If you as an R user find yourself wanting to use a Leaflet plugin that isn't directly supported in the R package, you can use the technique shown here to load the plugin yourself and invoke it using JS code.
| library(magrittr) | |
| library(httr) | |
| library(rvest) | |
| library(data.table) | |
| library(stringr) | |
| library(parallel) | |
| set_config(config(ssl_verifypeer = 0L)) | |
| list( |
| library(rvest) | |
| library(httr) | |
| library(stringr) | |
| library(magrittr) | |
| library(data.table) | |
| # library(quantmod) | |
| set_config(config(ssl_verifypeer = 0L)) | |
| # 取得上市股票類別 |
| import shapefile | |
| # read the shapefile | |
| reader = shapefile.Reader("my.shp") | |
| fields = reader.fields[1:] | |
| field_names = [field[0] for field in fields] | |
| buffer = [] | |
| for sr in reader.shapeRecords(): | |
| atr = dict(zip(field_names, sr.record)) | |
| geom = sr.shape.__geo_interface__ | |
| buffer.append(dict(type="Feature", \ |
| import fiona | |
| import fiona.crs | |
| def convert(f_in, f_out): | |
| with fiona.open(f_in) as source: | |
| with fiona.open( | |
| f_out, | |
| 'w', | |
| driver='GeoJSON', | |
| crs = fiona.crs.from_epsg(4326), |