Data Cardinality

Number of jobs created in the Senator and House Members’ Districts in North Carolina State.

Problem Statement

Several companies had created different jobs in different districts in North Carolina and beyond. A Survey was conducted on industrial extension jobs which revealed total number of jobs created in these districts. However, the results were not summarized in a way that politicians would easily see how their districts were affected by these. The Objective of this assignment was therefore to use data cardinality in analyzing and visualizing the jobs extension survey data. This would allow each Senator and House Member to see how many jobs were created in their districts and in the neighboring districts.

Analysis procedure

To address the problem, I used virtual computing lab’s ERIS ArcGIS Pro 2.9.1 which is hosted on Remote Desktop Web Client. Main tools used were excel to table, summarize table, join and relate, select by attributes, and export feature tool. Data used was NC job creation survey results which was provided by the course instructor, NC Senate and NC Houses Districts shapefiles, and USA Zip Code Points layer package.

Firstly, I exported the NC job creation survey results table to ArcGIS Pro using the Excel to table tool in the geoprocessing pane. Then I reviewed the table attributes and discovered that a number of zip codes were duplicate, hence needed to summarize the data to have a single zip code with a sum of jobs created. This was done using summary statistics, and a new table was created with zip code text field and the employ sum field. Secondly, using NC field in the USA ZIP Code Point layer, I run a selection by attribute, to select all ZIP Codes within North Carolina State only. This was followed by making a temporally layer from the selected features. Using this new NC State ZIP Code Layer, and Add Join tool, I added the ZIP Code table with the jobs created sum.

Last but not least, I used spatial join tool to join the NC Senate and House Members’ districts layers separately, with the Created Jobs ZIP Code layers intersects. This joined the boundaries with the point features that intersects with them. The target was to join the total created jobs field with the district’s layers. The final stage was to run a selection by attribute in both new layers which helped with eliminating all null features on employment sum variable. The final products were used to produce two professional maps, symbolized with graduating colors on employment sum variable.

Process Diagram

Results

Application and Reflection

Problem Statement: USAID/Malawi Health Office has its indicator data in excel file. The data is for the past three years, showing how different indicators have been preforming in different districts. USAID would like to know whether there has been an improvement in performance and whether certain districts are doing better than others, so as to capitalize on the low hanging fruits, and develop targeted interventions to improve the performance of underperforming districts.

Data needed: Health indicator performance results data for various districts, and Malawi districts boundary shapefile. The data will be obtained from USAID/Malawi GIS database.

Analysis procedure: I will start with data preparation, preparing the excel file, looking for common fields for joining. Then would use excel to table tool, to export the excel file into ArcGIS Pro. Then will do a one on one table join of the Malawi Districts Shapefile with the health indicators data table. Then I would copy the joined shapefiles on different map pages within the ArcGIS pro. Finally, I will use graduating color symbology on antenatal care visit indicator to showcase how different districts varies on that particular indicator, with each map showing only a particular year. The scale will be maintained, and the color ramp will also be maitained across the maps. I would add all these maps on one template to showcase the changes overtime.