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> d <- Daisi("Add Two Numbers")
[1] "Looking for Daisi: Add Two Numbers"
[1] "https://app.daisi.io/pebble-api/daisies/connect?name=Add%20Two%20Numbers"

> de <- d$compute(firstNumber = 5, secondNumber = 6)
[1] "Executing Daisi: 0a688b9a-49f7-42e9-8bab-5091b871f1a8"

> de$value()
[1] "Fetching Result: fa68ea3c-e73a-468e-8d51-a1f4ab824165"
[1] 11

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library(httr)

my_code <- paste(readLines("Downloads/text.R"), collapse = "%250A")

params <- list(
    backgroundColor = "rgba(100, 20, 250, 100)",
    code = my_code,
    theme = "dracula",
    exportSize = "3x"
)

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import requests
import time
import pandas as pd

# Get the list of coins from the API
r = requests.get("https://api.coingecko.com/api/v3/coins/list")
coin_list = r.json()

# Get all the ids
coin_ids = [x["id"] for x in coin_list]

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library(shiny)
library(shinythemes)
library(future)
library(promises)
library(tidyverse)
library(ipc)
library(future.callr)

plan(callr)

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library(tidyverse)
library(ggrepel)

ln <- read_csv("Investment_Bubble_Cycle_Line.csv") %>%
    mutate(Y = Y + 50 + 28)
cv <- read_csv("Investment_Bubble_Cycle.csv") %>%
    mutate(Y = Y + 50)

mapping = tibble(
    X = cv$X[c(20, 50, 70, 75, 105, 125, 138, 150, 175, 165, 185, 208, 225, 255, 280)],

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library(ggplot2)

ggplot(data = diamonds, aes(x = carat, y = price, colour = clarity)) +
    geom_point() +
    scale_y_continuous(labels = scales::dollar,
                       breaks = scales::breaks_width(2000)) +
    scale_x_continuous(breaks = scales::breaks_width(.5))

ggplot(data = diamonds, aes(x = carat, y = price, colour = clarity)) +
    geom_point() +

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library(tidyverse)
library(clean)

unclean_tbl <- tibble(
    Logical = c("Yes", "No", "Depends", "Unknown"),
    Factor = c("bachelor's", "Bachelor's Degree", "Master's Degree", "PhD"),
    Currency = c("$20", "$ 25", "26.02", "$27.0"),
    Numeric = c("~15", "about 10", "20", "15")
)

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library(tidyverse)
library(fable)

fable_series <- AirPassengers %>%
    as_tsibble() %>%
    model(
        ets = ETS(box_cox(value, 0.3)),
        arima = ARIMA(value),
        snaive = SNAIVE(value)
    ) %>%

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library(magick)
library(tidyverse)

im <- image_read("line.jpg")

im_proc <- im %>%
    image_channel("saturation") %>%
    image_threshold("white", "30%") %>%
    image_negate()

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library(tidyverse)

polygon_values <- tibble(
    id = 1:2,
    value = c(-2, 2)
)

polygon_positions <- tibble(
    id = c(1, 1, 1, 2, 2, 2, 2),
    x = c(1, 2, 3, 5, 6, 7, 6),