mikekeith52

import pandas as pd
import numpy as np
from scalecast.Forecaster import Forecaster
from pmdarima import auto_arima
import matplotlib.pyplot as plt
import seaborn as sns
sns.set(rc={'figure.figsize':(14,7)})

df = pd.read_csv('AirPassengers.csv')
f = Forecaster(y=df['#Passengers'],current_dates=df['Month'])

schochastics

library(shiny)
xy <- c(784,479) #output of grDevices::dev.size("px")
url <- "https://www.youtube.com/watch?v=Ef2jmf2vy00" #copy yt link here
url <- gsub("watch\\?v=","embed/",url)
ui <- fluidPage(
  HTML(paste0('<iframe width="',xy[1],'" height="',xy[2],'" src="',url,'" frameborder="0"></iframe>'))
)
server <- function(input, output, session) {
}

suissa

const groupBy = (xs, key) => xs.reduce((rv, x) => ({
  ...rv, [x[key]]: [...(rv[x[key]] || []), x]
}), {});