vnegi10

countries = ["France", "Russia", "Italy", "Iran", "India", "Germany", "Brazil"];
y, y_r, y_d = DataFrame(), DataFrame(), DataFrame() # separate empty dataframes to keep things simple

################## For total confirmed cases #####################
for country in countries    
    data_dfr = find_country(data_df,country); # returns a dataframe row 
    data_dfr = DataFrame(data_dfr);           # convert dataframe row back to a dataframe
    rows, cols = size(data_dfr);
    data_dfl = stack(data_dfr, 5:cols);       # convert dataframe into long format
    y[!,Symbol("$country")] = data_dfl[!,:value]

vnegi10

confirmed_cases = vec(convert(Array, last(y,1)))        # convert last dataframe row into a 1-D array
recovered_cases = vec(convert(Array, last(y_r,1)))
deaths          = vec(convert(Array, last(y_d,1)))

Y = Array{Float64,2}(undef, length(names(y_r)), 4)      # 2-D array with number of confirmed, recovered and deaths
Y[:,1] = deaths
Y[:,2] = confirmed_cases
Y[:,3] = recovered_cases
Y[:,4] = Y[:,2] - (Y[:,3] + Y[:,1])                     # number of currently infected = confirmed - (recovered + deaths)

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gr(size=(800,500))
display(groupedbar(names(y), Y, 
          bar_position = :dodge, 
          bar_width=0.75,
          ylabel = "Number of cases",
          xlabel = "Countries",
          label=["Deaths" "Confirmed" "Recovered" "Currently infected"],
          framestyle = :semi,
          formatter = :plain,
          legend = :topleft,

vnegi10

sort!(data_df_recovered,Symbol("7/31/20"),rev=true)                 # sort original DataFrame in descending order based on values in last column (latest date)
countries_sort_r = data_df_recovered[1:5,Symbol("Country/Region")]  # list of top 5 countries
latest_recovered_cases = data_df_recovered[1:5,Symbol("7/31/20")]   # number of recovered cases in top 5 countries

gr(size=(700,400))
display(bar(countries_sort_r, latest_recovered_cases,
    orientation = :h,
    xlabel = "Total number of recovered cases",
    ylabel = "Countries",
    legend = false,

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Top_five_anim = @animate for i in 50:length(names(data_df))  # loop through dates
    sort!(data_df, :($i), rev = true)                        # sort original DataFrame in descending order based on values in last column (latest date)
    countries_sort = data_df[1:5,Symbol("Country/Region")]   # list of top 5 countries
    latest_reported_cases = data_df[1:5,i]                   # number of reported cases in top 5 countries
    labels = string.(latest_reported_cases)
    
    gr(size=(800,500))
    bar(countries_sort, latest_reported_cases,
        ylabel = "Total number of confirmed cases",
        xlabel = "Countries",

vnegi10

function get_ratings_data(currency::String)

    date = Dates.today()
    main_dir = pwd()
    cd("data")

    # Look for present day's CSV file, if not found, download and save data to a new file
    if isfile("$(currency)_metrics_data_$(date).csv")
        metrics_df = CSV.File("$(currency)_metrics_data_$(date).csv") |> DataFrames.DataFrame
    else

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# Cleanup csv files from previous days
    try
        main_dir = pwd()
        cd("data")
        files = readdir()
        rx1 = r"data"
        rx2 = r".csv"
        for file in files
            ts = Dates.unix2datetime(stat(file).mtime)
            file_date = Date(ts)

vnegi10

function average_price_df(currency::String, df_in::DataFrame, df_out_price::DataFrame, df_out_candle::DataFrame)
    
    if isempty(names(df_out_price))
        df_out_price[!,:Date] = df_in[!,:Date]
    end    
    
    df_out_price[!,Symbol("$currency")] = (df_in[!,Symbol("open (EUR)")] + df_in[!,Symbol("high (EUR)")] + df_in[!,Symbol("low (EUR)")] + df_in[!,Symbol("close (EUR)")])/4

    candle_col = []
    for i in 1:size(df_in)[1]

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 # UI part of the tool
    app = dash()

    app.layout = html_div() do
        html_h1("Crypto Dashboard",
                style= (
                textAlign = "center",
                )
        ),
        html_div(

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function get_price_data_single(currency::String)
    
    df_out_price  = DataFrame()
    df_out_vol    = DataFrame()
    df_out_candle = DataFrame()
    date = Dates.today()

    main_dir = pwd()   
    cd("data")