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Table Operations

Introduction

Table operations are tools and methods used to interact with, manage, analyze, and visualize data that is stored in attribute tables. Knowing how to manipulate and use this data is an important skill, as it defines geographic features. In this lab, we practiced viewing, selecting, re-ordering, and updating tabular data. We learned simple operations like selecting by specific attributes, joining together existing tables, and creating new tables.

Resources Used

ArcGIS Pro

Process

In this lab, we were given census data of the United States Counties in a continental Albers projection, the soil contents in specific areas, and NAD83 meters coordinates. Before we began learning new skills, we made three maps to get used to the datasets given to us.

Medium Age of County Population

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Burglary Rates in 2001

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Population Density in 2000 (square miles)

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After seeing what data we had, reviewing prior cartography skills, and messing with the symbology, we began to learn new skills. The first step was learning how to select specific attributes. For this, we used the burglary rates in 2001. We wanted the burglaries to be normalized by the total population. In the attribute table, we created a new field. Then, using we calculated the field by building an expression, burglary rates divided by the population density multiplied by 100. Then, using the select specific attributes, we created a query, burglary rates greater than 1.037. These operations selected the counties in the United States that followed these rules.

Using the steps above, we created the following map.

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Next, we learned how to join two existing tables together. For this, we opened two separate attribute tables, one as a file and one as a data table. After examining each table, we needed to determine which variables might serve as keys for joining the tables together. There was a variable labeled Block Group in both data tables. Using the Join and Relate feature in ArcGIS Pro, we joined the data table to the file using the Block Group identifier. After following these steps, we had a complete dataset.

Using the steps above, we created the following map.

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Our final step was learning how to create new tables. For this, we used the soil layer, which showed the different soil types in specific areas. We needed to create a new data table to join to the soil file. Using the table feature in the Geoprocessing Pane, we create a table with the following fields:

soil type, long

name, text, length of 20

fertility class, double

drain class, double

After creating the new data table, we then assigned specific values and names to the features. Then, using the steps learned earlier, we joined together the two datasets using the common field, soil types. When creating the layout map, we used a quantile method for the 5 soil fertility classes. The following map was created.

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Summary

This lab focused on learning how to perform table operations in ArcGIS Pro to manage, analyze, and visualize geographic data stored in attribute tables. Using U.S. census county data in a continental Albers projection, soil data, and NAD83 meter coordinates, we first created maps showing median age, burglary rates in 2001, and population density in 2000 to become familiar with the datasets. We then practiced selecting and calculating attributes by normalizing burglary rates by population, creating a new field, building an expression, and selecting counties with rates greater than 1.037. Next, we learned to join tables by identifying a common “Block Group” field and using the Join and Relate tools to combine datasets. Finally, we created a new soil data table with specified fields, assigned values, joined it to the soil layer using soil type, and mapped soil fertility classes using a quantile classification method.

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