===Basic Horizontal Bar Chart===

This [[code:reports|code sample]] of a horizontal bar chart report.

Horizontal bar charts are ideal when you want to show a //discrete// value (such as an **on/off** or **open/closed/transitioning** status) over time.

Asset names vary wildly in terms of length. Because of this, we suggest placing your asset names //inside// the report rather than placing them on one of your axes.

{{hbar_basic.png|400}}

==Customising==

^Element^Replace With^
|[PROPERTY]|The name of the property you want to report on|

==The Code==

<code Python>
import os
import sys

sys.path.insert(0,os.path.dirname(os.path.dirname(__file__)))

import mplreport
import discretepatterns as dp
import pandas as pd
import datetime

@mplreport.ardireport("Sample Report")
def CreateReport(report,args):    
      
    #Create a page containing a single plot.
    fig,ax = report.CreatePage(1)

    #Print a title block for the page.
    report.Title()                   

    #Our AQL query goes here
    query = "('[PROPERTY]') PROPERTY ALLPOINTS"

    #Get the pandas data-frame with the results. Use the extended version that includes metadata.
    hist = report.FetchHistory(query)        
    df = hist.data

    #Use the 'Discrete Patterns' class to convert discrete data into
    #  time frames
    patterns = dp.DiscretePatterns()
    patterns.SetDataframe(df)
    patterns.Ready()        

    #Draw the bar chart

    indx = len(df.columns)-1
    for col in df.columns:
        #Convert a discrete value into a set of time frames
        frames = patterns.GetAllTimeframes(col)

        #Get a colour map to convert values to colours
        map = report.GetDiscreteColourMap(hist,col)

        #For every value found in the frame...
        for value in frames:
            #Draw bars for every time it had that value
            for frame in frames[value]:
                ax.broken_barh([(frame[0],frame[1] - frame[0])],(indx,0.9),color=map[value])
                
        indx -= 1

    #Draw in names
    indx = len(df.columns)-1
    for col in df.columns:
        ax.text(df.index[0] + datetime.timedelta(seconds=30), indx+0.18, col.replace(" [PROPERTY]","").strip(), c=(0,0,0,0.7))
        indx -= 1

    #Clear the Y axis
    ax.set_yticks(range(0,len(df.columns)))
    ax.set_yticklabels([""] * len(df.columns))        
    
    #Clean up and prettify        
    ax.set_ylabel("Drive")
    ax.set_xlabel("Time")    
    ax.margins(0,0)    
    report.TimeAxis(ax.xaxis)
    legend = report.GetDiscreteLegend(hist,df.columns[0])
    ax.legend(handles=legend[0])

    #Save this report out.
    report.Save()
</code>