Alan alanmarazzi

## defwrapper.clj
(ns defwrapper
  (:require [clojure.string :as str]))

(set! *warn-on-reflection* true)

(defn class-methods [^Class class]
  (seq (.getMethods class)))

(defn constructors [^Class klazz]
  (.getDeclaredConstructors klazz))

## pipeline.clj
(require '[clojure.core.async :as async]
         '[clj-http.client :as client]
         '[clojure.data.json :as json])

(def concurrency 5)

(let [in (async/chan)
      out (async/chan)
      request-handler (fn [url out*]
                          (async/go

## pokemon.csv

          
            #
            Name
            Type 1
            Type 2
            HP
            Attack
            Defense
            Sp. Atk
            Sp. Def
            Speed
            Generation
            Legendary

            
              1
              Bulbasaur
              Grass
              Poison
              45
              49
              49
              65
              65
              45
              1
              False

            
              2
              Ivysaur
              Grass
              Poison
              60
              62
              63
              80
              80
              60
              1
              False

            
              3
              Venusaur
              Grass
              Poison
              80
              82
              83
              100
              100
              80
              1
              False

            
              4
              Mega Venusaur
              Grass
              Poison
              80
              100
              123
              122
              120
              80
              1
              False

            
              5
              Charmander
              Fire
              
              39
              52
              43
              60
              50
              65
              1
              False

            
              6
              Charmeleon
              Fire
              
              58
              64
              58
              80
              65
              80
              1
              False

            
              7
              Charizard
              Fire
              Flying
              78
              84
              78
              109
              85
              100
              1
              False

            
              8
              Mega Charizard X
              Fire
              Dragon
              78
              130
              111
              130
              85
              100
              1
              False

            
              9
              Mega Charizard Y
              Fire
              Flying
              78
              104
              78
              159
              115
              100
              1
              False

## Basic_R.R
# As a primer you saw also earlier that I wrote
# some text in the code, but it wasn't evaluated.
# These are comments, you can use them by simply
# using "#" before the text.

###### I can add also more "#" to draw the attention
# on that comment.

# Assign names
# We can do math with R as we would do in a simple calculator

## R_check.R
# Generate some random number
x <- runif(10)
y <- runif(10)

# Print generated numbers
x
y

# Sum the two vectors
x + y

## R_intro.R
# Read data from csv
df <- read.csv("some_data.csv")

# Make a plot of the data
plot(df$debt, df$gdp)

# Fit a linear regression
lm(gdp ~ debt, data = df)

## Plotting R code for previous chart.R
library(ggplot2) # This loads ggplot2 package, it's better and easier than base R plot

# This is the colors' palette used in the chart
pal <- c("#0E37B1", "#FF4100", "#00B65E", "#FFAE00", "#394C86", "#C66746", "#318A5F", "#C69E46")

# Here the code for the plot [don't worry, in next posts I'll
# explain better every line of code, just keep following me ;) ]
ggpoints <- ggplot(df, aes(HC, LC, color = Country))+
    geom_point(size = 3, shape = 16)+
    scale_color_manual(values = pal)+
	(ns defwrapper
	(:require [clojure.string :as str]))

	(set! warn-on-reflection true)

	(defn class-methods [^Class class]
	(seq (.getMethods class)))

	(defn constructors [^Class klazz]
	(.getDeclaredConstructors klazz))
	(require '[clojure.core.async :as async]
	'[clj-http.client :as client]
	'[clojure.data.json :as json])

	(def concurrency 5)

	(let [in (async/chan)
	out (async/chan)
	request-handler (fn [url out*]
	(async/go
#	Name	Type 1	Type 2	HP	Attack	Defense	Sp. Atk	Sp. Def	Speed	Generation	Legendary
1	Bulbasaur	Grass	Poison	45	49	49	65	65	45	1	False
2	Ivysaur	Grass	Poison	60	62	63	80	80	60	1	False
3	Venusaur	Grass	Poison	80	82	83	100	100	80	1	False
4	Mega Venusaur	Grass	Poison	80	100	123	122	120	80	1	False
5	Charmander	Fire		39	52	43	60	50	65	1	False
6	Charmeleon	Fire		58	64	58	80	65	80	1	False
7	Charizard	Fire	Flying	78	84	78	109	85	100	1	False
8	Mega Charizard X	Fire	Dragon	78	130	111	130	85	100	1	False
9	Mega Charizard Y	Fire	Flying	78	104	78	159	115	100	1	False
	# As a primer you saw also earlier that I wrote
	# some text in the code, but it wasn't evaluated.
	# These are comments, you can use them by simply
	# using "#" before the text.

	###### I can add also more "#" to draw the attention
	# on that comment.

	# Assign names
	# We can do math with R as we would do in a simple calculator
	# Generate some random number
	x <- runif(10)
	y <- runif(10)

	# Print generated numbers
	x
	y

	# Sum the two vectors
	x + y
	# Read data from csv
	df <- read.csv("some_data.csv")

	# Make a plot of the data
	plot(df$debt, df$gdp)

	# Fit a linear regression
	lm(gdp ~ debt, data = df)
	library(ggplot2) # This loads ggplot2 package, it's better and easier than base R plot

	# This is the colors' palette used in the chart
	pal <- c("#0E37B1", "#FF4100", "#00B65E", "#FFAE00", "#394C86", "#C66746", "#318A5F", "#C69E46")

	# Here the code for the plot [don't worry, in next posts I'll
	# explain better every line of code, just keep following me ;) ]
	ggpoints <- ggplot(df, aes(HC, LC, color = Country))+
	geom_point(size = 3, shape = 16)+
	scale_color_manual(values = pal)+