#Non-mathematical Introductions
- http://gcn.com/articles/2014/01/09/topographical-data-analysis.aspx
- https://www.simonsfoundation.org/quanta/20131004-the-mathematical-shape-of-things-to-come/
#Videos
library(RemixAutoML) | |
library(data.table) | |
########################################### | |
# Prepare data for AutoTS()---- | |
########################################### | |
# Load Walmart Data from Dropbox---- | |
data <- data.table::fread("https://www.dropbox.com/s/2str3ek4f4cheqi/walmart_train.csv?dl=1") |
Sub WorkbooksSaveAsCsvToFolder() | |
'UpdatebyExtendoffice20181031 | |
Dim xObjWB As Workbook | |
Dim xObjWS As Worksheet | |
Dim xStrEFPath As String | |
Dim xStrEFFile As String | |
Dim xObjFD As FileDialog | |
Dim xObjSFD As FileDialog | |
Dim xStrSPath As String | |
Dim xStrCSVFName As String |
from bs4 import BeautifulSoup | |
import requests | |
import requests.exceptions | |
from urllib.parse import urlsplit | |
from urllib.parse import urlparse | |
from collections import deque | |
import re | |
url = "https://scrapethissite.com" | |
# a queue of urls to be crawled |
nobs <- 4000 | |
pb <- round(runif(n=1, min=0.1, max=0.8),1) | |
August <- rbinom(n=nobs, size=1, prob=pb) | |
pb <- round(runif(n=1, min=0.1, max=0.8),1) | |
September <- rbinom(n=nobs, size=1, prob=pb) | |
pb <- round(runif(n=1, min=0.1, max=0.8),1) | |
October <- rbinom(n=nobs, size=1, prob=pb) | |
pb <- round(runif(n=1, min=0.1, max=0.8),1) | |
November <- rbinom(n=nobs, size=1, prob=pb) | |
pb <- round(runif(n=1, min=0.1, max=0.8),1) |
#Non-mathematical Introductions
#Videos
library(idbr) # devtools::install_github('walkerke/idbr') | |
library(ggplot2) | |
library(animation) | |
library(dplyr) | |
library(ggthemes) | |
idb_api_key("Put your Census API key here") | |
male <- idb1('CH', 2016:2050, sex = 'male') %>% | |
mutate(POP = POP * -1, |
library(ggplot2); | |
library(grid); | |
data(iris) | |
x <- jitter(iris[,c('Sepal.Length')]) | |
y <- jitter(iris[,c('Sepal.Width')]) | |
z <- factor(iris[,c('Species')]) | |
# The color blind palette without black: |
""" | |
Demonstrates how to use the blocking scheduler to schedule a job that executes on 3 second | |
intervals. | |
""" | |
from datetime import datetime | |
import os | |
from apscheduler.schedulers.blocking import BlockingScheduler |
My first examples with [***knitr***](http://yihui.name/knitr/) | |
----------------------------------------- | |
Let's include some simple R code: | |
```{r} | |
1+2 | |
``` | |
That worked. | |
Let's include a plot: | |
```{r fig.width=4, fig.height=4} |
### DATA SECTION | |
library(data.table) | |
## Read data with 'data.table::fread' | |
input <- fread("wu03ew_v1.csv", select = 1:3) | |
setnames(input, 1:3, new = c("origin", "destination","total")) | |
## Coordinates | |
centroids <- fread("msoa_popweightedcentroids.csv") | |
## 'Code' is the key to be used in the joins |