lukereding

0214-lreding:deck_gl_geojson lreding$ ap run
+ yarn add deck.gl
yarn add v0.23.2
warning No license field
[1/4] 🔍  Resolving packages...
[2/4] 🚚  Fetching packages...
[3/4] 🔗  Linking dependencies...
[4/4] 📃  Building fresh packages...
warning Your current version of Yarn is out of date. The latest version is "0.23.3" while you're on "0.23.2".
success Saved 1 new dependency.

lukereding

swagger: '2.0'
info:
  description: >-
    This is a simple example of a REST API deployed on Anaconda Enterprise and
    documented with Swagger UI.
  version: 2017.06.02
  title: quotes
  termsOfService: 'http://swagger.io/terms/'
  contact:
    email: lreding@continuum.io

lukereding

swagger: '2.0'
info:
  description: >-
    This API implments some simple natural language processing tasks like
    tokenization, sentiment analysis, and retrieving parts of speech from text.
  version: 2017.06.08
  title: NLP with Anaconda
  termsOfService: ''
  contact:
    email: lreding@continuum.io

lukereding

random_csv = "http://datadryad.org/bitstream/handle/10255/dryad.37977/Cranby%20E4%20pheno.csv?sequence=1"

# read in a csv
df <- read.csv(random_csv)

# print it to the console
print(df)

# print the raw characters from the csv file to the console
readLines(random_csv)

lukereding

swagger: '2.0'
info:
  description: >-
    This API implments some simple natural language processing tasks like
    tokenization, sentiment analysis, finding the most common words, and
    retrieving parts of speech from text.
  version: 2017.06.14
  title: Natural Language Processing with Anaconda
  termsOfService: ''
  contact:

lukereding

df <- read_csv("http://datadryad.org/bitstream/handle/10255/dryad.152300/forDryad.csv?sequence=1")
df %<>% unite(uni, source, target)

edges <- df %>% 
  group_by(uni) %>%
  count %>% 
  separate(col = "uni", into = c("source", "target"), sep = "_")
edges <- rename(edges, number = n)

net <-graph_from_data_frame(edges)

lukereding

library(ggplot2)
library(cowplot) # github version

# create dataframe with x and y with different ranges
df <- data.frame(x = rnorm(20, mean = 5, sd = 2), y = rnorm(20, mean = 20, sd = 5))

# create scatterplot
p <- ggplot(df, aes(x = x, y = y)) +
  geom_point()

lukereding

data_frame(x=1:10)  %>%  
  mutate(
    # x2 = x*2,  
    x3 = x*3) %>%  
  filter(x>5)  

lukereding

#!/usr/bin/env bash

# this script downloads an example animation from the internet and creates looped version of the animation that you could then use in a mate choice study
# the advantage of the script as opposed to doing this in something like iMovie:
### time. On my computer this script takes <30 seconds to execute. Doing this in iMovie could easily take half an hour.
### repeatability. I can send this script to you and you can make the video yourself.
### easy to remake videos when you make a mistake
### easy to keep track of what you've done. A plain text script like this allows you do _version control_ your work, allowing you to revert to a previous version and always know when you changed parts of your code

# make a directory to keep things tidy

lukereding

# the goal:
## download the animation
## use ffmpeg to make it playable
## change the speed of the animation
## randomally change the speed of the animation
## concatenate multiple speeds together

# make a directory to keep things tidy
mkdir create_video
cd create_video