Difference between revisions of "Two Eyes One Pizza Data"
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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. | 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. | ||
| + | ==<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="font-family:Helvetica;font-size:16px"> | ||
| + | 5 Competitors are identified and they are Dominos Pizza, Napolean Pizza, Mcdonalds, KFC and MosBurger. Hence, these competitors branches location have to be extracted from "Restaurant 5800" and to be aggregated. | ||
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| + | [[File:Mac.png|thumb]] | ||
==<div style="background: #8b1209; padding: 15px; line-height: 0.3em; text-indent: 15px; font-size:18px; font-family:Helvetica"><font color= #FFFFFF>Aggregating POIs into each trade area (Script)</font></div>== | ==<div style="background: #8b1209; padding: 15px; line-height: 0.3em; text-indent: 15px; font-size:18px; font-family:Helvetica"><font color= #FFFFFF>Aggregating POIs into each trade area (Script)</font></div>== | ||
Revision as of 10:22, 21 October 2019
Contents
Preliminary Data Observations
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.
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.
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.
Extracting Competitor's Data Points
5 Competitors are identified and they are Dominos Pizza, Napolean Pizza, Mcdonalds, KFC and MosBurger. Hence, these competitors branches location have to be extracted from "Restaurant 5800" and to be aggregated.
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
After the aggregation of POIs into each trade area, below is the screenshot of the columns for a particular trade area.
Comments
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