Difference between revisions of "Two Eyes One Pizza Data"

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==<div style="background: #8b1209; padding: 15px; line-height: 0.3em; text-indent: 15px; font-size:18px; font-family:Helvetica"><font color= #FFFFFF>Preliminary Data Observations</font></div>==
 
==<div style="background: #8b1209; padding: 15px; line-height: 0.3em; text-indent: 15px; font-size:18px; font-family:Helvetica"><font color= #FFFFFF>Preliminary Data Observations</font></div>==
 
<div style="font-family:Helvetica;font-size:16px">
 
<div style="font-family:Helvetica;font-size:16px">
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International Food Chain (IFC) is a leading brand in its sector, with over 18000 outlets worldwide and an ever-growing presence in the global market. In Taiwan alone, IFC has over 240 branches and are constantly expanding.
 
  
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However, as the franchise grows bigger, so does its challenges. One of the challenges involves the lack of an analysis to efficiently compare the performance of each chain to one another.
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<What data we have here>
  
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Leveraging on this fact, our group aims to digitalise the data and conduct in-depth analysis on each branch. We hope to track the performance of each chain in relation to Point-Of-Interests surrounding each chain, uncovering and comprehending phenomena, with the aid of spatial data.
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<br/><br/>
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Steps:
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# Align to Geometry and Coordinate Reference System for all files: EPSG:3828
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# Extracting each POI from the different shp files
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# Formation of polygons for each branch to align to ppt slides' trade area
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#
  
 
==<div style="background: #8b1209; padding: 15px; line-height: 0.3em; text-indent: 15px; font-size:18px; font-family:Helvetica"><font color= #FFFFFF>Extracting Competitor's Data Points</font></div>==
 
==<div style="background: #8b1209; padding: 15px; line-height: 0.3em; text-indent: 15px; font-size:18px; font-family:Helvetica"><font color= #FFFFFF>Extracting Competitor's Data Points</font></div>==

Revision as of 10:30, 21 October 2019

2e1p.png

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PROPOSAL

 

DATA TRANSFORMATION

 

POSTER

 

APPLICATION

 

RESEARCH PAPER


Preliminary Data Observations

<What data we have here>



Steps:

  1. Align to Geometry and Coordinate Reference System for all files: EPSG:3828
  2. Extracting each POI from the different shp files
  3. Formation of polygons for each branch to align to ppt slides' trade area

Extracting Competitor's Data Points

5 Competitors are identified and they are Dominos Pizza, Napolean Pizza, Mcdonalds, KFC and MosBurger. These data points are crucial in our analysis as they may have a correlation with the sales data. Hence, these competitors branches location have to be extracted from "Restaurant 5800".

After extraction, they are exported as layers in the geopackage to be used for aggregation.

Mac.png

Aggregating POIs into each trade area (Script)

It is an exhausting task to aggregating each of the POIs into each trade area using the "Count Points in Polygon" tool.

The batch processing tool was tried but it is unable to append each newly created POI into an existing geopackage. Hence, a python script was written and it ran under QGIS's Python Console. It utilised "processing.run('qgis:countpointsinpolygon', parameters)" function, an inbuilt function by QGIS.

Learn more about the function here: https://docs.qgis.org/2.8/en/docs/user_manual/processing_algs/qgis/vector_analysis_tools/countpointsinpolygon.html

Py.png

After the aggregation of POIs into each trade area, below is the screenshot of the columns for a particular trade area.

Ta.png

Comments

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