vnegi10

function raw_to_df(raw_data)
    df = DataFrame(raw_data[1])
    df_names = Symbol.(vcat(raw_data[2]...))
    df = DataFrames.rename(df, df_names)

    timestamps = df[!,:timestamp]

    select!(df, Not([:timestamp]))

    for col in eachcol(df)

vnegi10

function plot_price_vol_data(index::Int64, duration::Int64, window::Int64)

    # Retrieve data from various helper functions    
    Price_df, Candle_df, Vol_df = get_price_data_single(currencies[index])    
        
    # Make sure that duration does not exceed the number of rows - max(windows) in the DataFrame
    # This allows calculation of MA for the longest duration
    if duration > size(Price_df)[1]-maximum(windows)
        duration = size(Price_df)[1]-maximum(windows)
    end

vnegi10

callback!(
        app,
        Output("graph", "figure"),
        Input("mode_ID", "value"),
        Input("pair_ID", "value"), 
        Input("window_ID", "value"),
        Input("duration_ID", "value"),
    ) do mode_ID, pair_ID, window_ID, duration_ID
        t1, t2, t3, t4, t5, t6 = plot_price_vol_data(pair_ID, duration_ID, window_ID)
        

vnegi10

# GitHub link	
const URL = "https://raw.githubusercontent.com/vnegi10/Health_data_analysis/master/data"
	
# CSV files from Samsung Health app	
files = ["com.samsung.shealth.tracker.pedometer_day_summary.202110031456.csv", 
       "com.samsung.shealth.tracker.heart_rate.202110031456.csv",
       "com.samsung.health.floors_climbed.202110031456.csv"]	

# Function to generate url	
gen_url(file::String, url::String=URL) = joinpath(url, file)

vnegi10

# 1 - Check size of the DataFrame, returns (rows, columns)
size(df_pedometer_raw)

# 1 - Result
# (3221, 20)

# 2- List column names
names(df_pedometer_raw)

# 2- Result

vnegi10

# Create an independent copy
df_pedometer = deepcopy(df_pedometer_raw)

# Set format for the DateTime object
datef = dateformat"y-m-d H:M:S.s"

# Convert create_time column from string into DateTime objects
df_pedometer[!, :create_time] = DateTime.(df_pedometer_raw[!, :create_time], datef)

# Convert distance into km and time into minutes

vnegi10

cumul_distance = Float64[]
day_type, day, month = (String[] for i = 1:3)	 
year = Int64[]	    

for i = 1:size(df_pedometer)[1]
    push!(cumul_distance, sum(df_pedometer[!, :distance][1:i]))
    push!(day, Dates.dayname(df_pedometer[!, :create_time][i]))
    push!(month, Dates.monthname(df_pedometer[!, :create_time][i]))
    push!(year, Dates.year(df_pedometer[!, :create_time][i]))
          

vnegi10

df_pedometer_filter = df_pedometer |> 

@filter(_.create_time > start_date &&  _.create_time < end_date) |> DataFrame

vnegi10

df_pedometer_filter |> @vlplot("mark"={:area, "line" = {"color" = "seagreen"},
        				               "color"={"x1"=1, "y1"=1, "x2"=1, "y2"=0,
           				             "gradient"=:linear, "stops" = [
               			           {"offset"=0, "color"="white"},
                		           {"offset"=1, "color"="green"}]}}, 
	x = {:create_time, "axis" = {"title" = "Time", "labelFontSize" = 12, "titleFontSize" = 14}, "type" = "temporal"}, 
	y = {:step_count, "axis" = {"title" = "Daily steps", "labelFontSize" = 12, "titleFontSize" = 14 }}, 
	width = 750, height = 500, 
	"title" = {"text" = "Daily steps from $(Date.(start_date)) to $(Date.(end_date))", "fontSize" = 16})

vnegi10

figure2 = df_pedometer_filter |> 

@vlplot(:bar, 
	x = {:step_count, "axis" = {"title" = "Number of steps", "labelFontSize" = 12, "titleFontSize" = 14}, "bin" = {"maxbins" = bins1}}, 
	y = {"count()", "axis" = {"title" = "Number of counts", "labelFontSize" = 12, "titleFontSize" = 14 }}, 
	width = 850, height = 500, 
	"title" = {"text" = "Step count distribution from $(Date.(start_date)) to $(Date.(end_date))", "fontSize" = 16},
	color = "year:n")