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import numpy as np
import pandas as pd

#load data from your preferred source
data = pd.read_csv("PATH/TO/FILE/futures_rolling.csv", index_col = [0], parse_dates=True)

june_21 = data["VX-2021M"]
july_21 = data["VX-2021N"]

def perpetual_rollover(previous_futures, next_futures, roll_date, number_of_rolls):

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import pandas as pd

#load data from your preferred source
data = pd.read_csv("PATH/TO/FILE/futures_rolling.csv", index_col = [0], parse_dates=True)

june_21 = data["VX-2021M"]
july_21 = data["VX-2021N"]

def proportional_adjustment(previous_futures, next_futures, roll_date):
    roll_proportion = next_futures[roll_date]/previous_futures[roll_date]

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import pandas as pd

#load data from your preferred source
data = pd.read_csv("PATH/TO/FILE/futures_rolling.csv", index_col = [0], parse_dates=True)

june_21 = data["VX-2021M"]
july_21 = data["VX-2021N"]

def panama_adjustment(previous_futures, next_futures, roll_date):
    roll_gap = next_futures[roll_date] - previous_futures[roll_date]

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#load R packages
library(shiny)
library(leaflet)
library(RColorBrewer)
library(xts)
library(rgdal)


#helper function for choropleth animation
setShapeStyle <- function( map, data = getMapData(map), layerId,

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sliderInput("dateSel", "Date",
            min = min(covidData$Date_reported),
            max = max(covidData$Date_reported),
            value = min(covidData$Date_reported),
            step = 1,
            timeFormat = "%d %b %y",
            animate = animationOptions(interval = 500, loop = FALSE)
)

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#create choropleth map
leaflet(world_spdf) %>% 
  addTiles()  %>% 
  setView(lat = 0, lng = 0, zoom=2) %>%
  
  addPolygons( 
    layerId = ~ISO2,
    fillColor = ~colorPalette(Cases),
    stroke = TRUE, 
    fillOpacity = 1, 

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#create map with circle markers
leaflet(world_spdf) %>% 
  addTiles()  %>% 
  setView(lat = 0, lng = 0, zoom=2) %>%
  
  addCircleMarkers(lng = ~LON,
                   lat = ~LAT,
                   radius = ~log(Cases) * 2,
                   weight = 1,
                   opacity = 1,

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library(leaflet)
library(rgdal)
library(RColorBrewer)

#load spatial data
world_spdf <- readOGR( 
  dsn = getwd() , 
  layer = "TM_WORLD_BORDERS_SIMPL-0.3",
  verbose = FALSE
)

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covidData <- read.csv("https://covid19.who.int/WHO-COVID-19-global-data.csv", fileEncoding="UTF-8-BOM", stringsAsFactors = FALSE)
covidData <- na.omit(covidData)

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library(rgdal)

#you only have to do this once!
download.file("http://thematicmapping.org/downloads/TM_WORLD_BORDERS_SIMPL-0.3.zip" , destfile="world_shape_file.zip")
system("unzip world_shape_file.zip")

#loading the world borders spatial polygons data frame
world_spdf <- readOGR( 
  dsn= getwd() , 
  layer="TM_WORLD_BORDERS_SIMPL-0.3",