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ZeccaLehn / downloadTree.md
Last active November 17, 2017 02:16
Download all files within directory tree in Python

Creating Zips

import shutil
import os

cwd = os.getcwd()
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ZeccaLehn / binomialCoins
Created October 19, 2017 08:26
Likelihood and coin-flips (Combinatorics and Likelihood Connection using #rstats)
### Likelihood of getting 3 heads out of 8 flips given a fair coin
n = 8
k = 3
steps = 10001 # Non zero ending to get likelihood; best if > 10000
p_grid = seq(0,1,length.out = steps)
prior = rep(1, steps)
likelihood = dbinom(k, n, prob = p_grid)
# unstd.posterior = likelihood*prior
# posterior = unstd.posterior/sum(unstd.posterior)
# plot(p_grid, posterior)
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ZeccaLehn / constrainedR.md
Created October 12, 2017 09:27
Constrained Optimization in R 
library(mosaic)

f <- makeFun(x^2 + y ~ x & y)
g <- makeFun(x^2 - y^2 ~ x & y)

  # levelset <- 10
  # plotFun(f(x,y) ~ x & y, xlim = range(-10, 10),
  #         levels = levelset, ylim = range(-10, 10), filled = F)
  # plotFun(g(x,y) ~ x & y, levels = levelset,  xlim = range(-10, 10),
@ZeccaLehn
ZeccaLehn / installR
Created October 11, 2017 04:55
Install and Load Multiple Packages R
packages <- c("twitteR", "dismo", "maps", "ggplot2")
installAll <- packageList[!packages %in% rownames(installed.packages())]
if(installAll){install.packages(installAll, repos = "http://cran.us.r-project.org")} else {print("No Packages Installed")}
lapply(packages, library, character.only = TRUE)
@ZeccaLehn
ZeccaLehn / dynamicProbability.md
Created October 1, 2017 21:19
Binomial Probabilities in R using Manipulate Package 
binomProbs <- function(w, n, propStep){

  # print(w)
  # print(n)
  # print(propStep)
  
  plot(seq(0, 1, propStep), dbinom(w, n, prob = seq(0,1, propStep)), xlim = c(0, 1),
       xlab = "", ylab = "")
 points(seq(0, 1, propStep),
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ZeccaLehn / monteHall.md
Last active October 1, 2017 04:48
Monte Hall Simulation -- Goat or Ferrari?
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ZeccaLehn / returnList.md
Last active September 29, 2017 17:57
Function Returning List of Multiple Objects in R 
# Function
xylist <- function(start, finish){
  
  x <- seq(start, finish)
  y <- seq(start, finish)^2
  
  return(list("x" = x, "y" = y))
  
}
@ZeccaLehn
ZeccaLehn / mtcars.csv
Last active July 7, 2023 05:53
Python Download CSV from Gist (MTCARS DataSet)
mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21 6 160 110 3.9 2.62 16.46 0 1 4 4
Mazda RX4 Wag 21 6 160 110 3.9 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108 93 3.85 2.32 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360 175 3.15 3.44 17.02 0 0 3 2
Valiant 18.1 6 225 105 2.76 3.46 20.22 1 0 3 1
Duster 360 14.3 8 360 245 3.21 3.57 15.84 0 0 3 4
Merc 240D 24.4 4 146.7 62 3.69 3.19 20 1 0 4 2
Merc 230 22.8 4 140.8 95 3.92 3.15 22.9 1 0 4 2
@ZeccaLehn
ZeccaLehn / Final_Money_100.csv
Last active September 25, 2017 23:19
Census & Money 2017 Top 100 Places (Fips/Zips/Lat/Long/County/State)
place stateAbbr Rank county state stateFips countyFips placeFips censusPlaceType placeSym zip latitude longitude
Fishers IN 1 Hamilton INDIANA 18 57 23278 Incorporated Place A 46037 39.96 -85.94
Allen TX 2 Collin TEXAS 48 85 1924 Incorporated Place A 75002 33.092846 -96.62447
Monterey Park CA 3 Los Angeles CALIFORNIA 6 37 48914 Incorporated Place A 91754 34.048207 -118.14161
Franklin TN 4 Williamson TENNESSEE 47 187 27740 Incorporated Place A 37064 35.893823 -86.89919
Olive Branch MS 5 DeSoto MISSISSIPPI 28 33 54040 Incorporated Place A 38654 34.954106 -89.83743
Dickenson ND 6 Stark NORTH DAKOTA 38 89 19620 Unknown Unknown 58601 46.879176 -102.789624
Lone Tree CO 7 Douglas COLORADO 8 35 45955 Incorporated Place A 80130 39.541571 -104.92152
North Arlington NJ 8 Bergen NEW JERSEY 34 3 52320 Unknown Unknown 7031 40.791895 -74.13254
Schaumburg IL 9 Cook ILLINOIS 17 31 68003 Unknown Unknown 60159 41.811929 -87.68732
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ZeccaLehn / aggregateVersusMerge.R
Last active June 19, 2017 22:18
Aggregate versus merge MTCARS with R data.table
###### MTCARS Merging and Aggregation Example ######
### Prepare data and load library
library(data.table)
mtcarsDt <- as.data.table(mtcars); mtcarsDt
mtcarsDt <- cbind(carBrand = rownames(mtcars), mtcarsDt); mtcarsDt
## Use list to aggregate
aggregateMtCars <- mtcarsDt[, list(nAgg = .N, meanHPagg = mean(hp)), by = c("gear", "am")]
aggregateMtCars