How many increasing subsets can be created


Almost all GIS data is saved and displayed in the form of a simple database table. For example, feature classes are tables with a shape attribute (an attribute in a table is also called a field or column), grids can be displayed as tables with attributes, and most GIS databases have stand-alone tables with attributes for which Relationships with other tables can be established via a common attribute. When creating a database or performing analysis, most of the time is spent managing tables, adding and calculating new attributes, copying tables or table rows from one location to another, converting tables with text strings for coordinate values ​​to Features, establishing relationships between tables, or calculating summary statistics.

In some analyzes, you need to extract GIS data in the form of tables for other applications, or you need tabular data from another application as input to the GIS. Often times, geoprocessing steps modify and combine datasets to create a feature class with many attributes derived from other data. These can be selected or combined to produce tabular results.

Creation of GIS data from tables

Joining tables

A common technique is to join tables of data (such as demographic or medical statistics) to a number of geographic features to represent them graphically. This requires that the table in question and the geographic features share a key field, such as a name or ID code.

The following example shows how GIS features can be assigned additional attributes by connecting to data from another table. This Iowa counties feature class has name and FIPS code attributes that can be used as key fields in a table join.

The Standalone Table provides information about the soybean harvest for each Iowa county. It also contains name and FIPS code attributes that can be used to connect to the county features.

After the harvest data is connected to the county features, you can symbolize, label, or select the county features using the fields from the harvest table.

When connecting data from different sources, it is essential that the data types and data values ​​of the key fields match exactly. If one field is of a numeric type while the other contains text, the fields cannot be merged. To fix this problem, you can create a new field in one of the tables that has the same data type as the field in the other table, and then calculate the values ​​from the mismatched field in the new, matching field. If a key value is misspelled, spelled differently, or contains misspellings or additional characters (such as a leading space), the records with the mismatched keys are also not joined.

Create features from tables

Another common practice is to build spatial information from tabular data.

XY events

The simplest of these methods is to create an XY event layer from a table that has an X coordinate field and a Y coordinate field. The following example shows how a simple table of coordinates and other data can be converted to point events.

The point events created from the table behave like a feature class and can be symbolized and labeled using the attributes in the table.


You can also create points by matching values ​​in a table against a reference feature class. A convenient way to do this is by geocoding, where the table contains address information and the reference feature class contains street and county information.

The following example shows a point created from an address, where the address was geocoded using the reference street data.

Linear referencing

Another possibility is to compare locations based on distances along a line. This process is known as linear referencing. This method can be used to create point events at a specified distance along a line or line events that follow the line from one location to another.

The following example shows point events generated by matching a table of distance values ​​and route identifiers with a line feature class that contains route features with metrics.

The following example shows line events generated by matching a table of from and to metrics and route identifiers to a line feature class that contains route features with metrics.

Analysis of tabular data

A common part of analyzing tabular data is to determine how many items belong to a particular category, or to examine the distribution of values ​​for a range of items. Often the elements to be examined are surrounded by many other elements that are slightly (or strongly) different from them. To determine features based on these differences, it is often necessary to combine data from different sources by joining tables or creating spatial joins and overlays. Then values ​​must be selected in fields and calculated.

Determine the number

Occasionally, the features in the GIS have attributes that should be analyzed by finding the sum of fields for selected features or the frequency of a particular type of feature. You can use the Statistics and Frequency tools in the Statistics toolbox to calculate these statistics for one or more fields and summarize the results according to the values ​​in another field. This can be useful for both reporting and performing analysis.

Calculating frequency with the Frequency tool allows you to determine how many items fall into a given category. For example, you can run the tool on a series of parcels to see how many of them belong to particular land use categories. Examining the frequency distribution for the category data is an important first step in many analyzes.

This frequency table shows that there are almost five times as many residential parcels as office parcels and that only a small proportion of the parcels fall into the categories of utilities and authorities.

Frequency information for a field in a table can also be found in ArcMap by right-clicking the field heading in the table window and selecting Statistics.

Investigate the distribution of values

You can use the summary statistics to quantify how many members of a population can be assigned to certain features. Instead of just running Frequency and determining how many parcels of each type there are, you can run the Parcel Statistics tool to find or measure the total area (sum) of the parcels in each category determine how large the parcels of each type are on average (mean).

You can see from this table of summary statistics that while there are more commercial parcels than government parcels, they both occupy a similar area of ​​the urban area. This suggests that government and utility parcels tend to be larger than office, residential, and industrial parcels.

You can also use the Summary Statistics tool to examine the distribution of values ​​for multiple features. For example, you can compare minimum and maximum height values ​​for different types of plants in the study area, the price ranges for buildings of a particular type in an area, or the average amounts by which the prices for buildings of that type differ from the average price (the standard deviation).

You can also summarize tables in ArcMap by right-clicking the field column heading in the table window and then selecting Field Statistics.

For more information about working with statistics in GIS, see Statistical Analysis.

Counting records

Occasionally, you need to know how many records there are in a table or selection. This information can be used, for example, in a model or script that automates an analysis or reporting process. The Get Count tool returns the number of features or rows in a feature class, table, or layer. Selection areas, table views and layers based on queries are taken into account. You can use the Get Count tool in a loop script that buffers a position as the distance increases and selects the features in the buffer until a certain number of features are selected.

Management of table data

Calculating values

The Calculate Field tool mathematically combines or changes values ​​in one or more fields. These calculations can be very simple, for example when a given field is calculated as "23" for all features or as "true" for all selected features, or when values ​​in multiple fields are combined. You can e.g. For example, you can divide a population field by an area field to get population density values, or you can concatenate text values ​​for house number, street name, and street type in a single address field. Often times, you'll use the Add Field tool to add a new field to hold the results of the calculation.

Joining tables

The Add Connection tool is often used to combine derived tabular data with other data in one analysis step. When tables share a key value (such as a feature ID or name), they can be joined. The data in both tables can then be analyzed at the same time. This tool can only be used with feature layers or table views that are in the ArcMap table of contents, or with the Make Feature Layer and Make Table View tools. The connection is temporary and only exists for the duration of the session. You can use the Copy Features or Copy Targets tools to save the merged results to a new feature class or table, or to export the data to ArcMap.

Attribute indexes

Indexing a field allows rows with that attribute to be selected more efficiently. You can use the Add Attribute Index tool to index a field.

Subtypes and attribute domains

When a table is stored in a geodatabase, subtypes can be created for the features and attributes. You can use subtypes to divide feature classes and tables into logical groups based on attribute values. It also allows you to work with a subset of features in a feature class or rows in a table. With the help of subtypes, these subsets can be assigned uniform attributes and uniform behavior.

Learn more about tools for creating and managing subtypes

Domains provide a method of defining ranges of values ​​that can be used for multiple attribute fields. You can use domains to ensure data integrity by limiting the number of possible values ​​for certain fields.

Learn more about tools for creating and managing domains

Table views

A table is a physical table on disk or in a database. A table view is a temporary table in computer memory that can be used like a physical table. Typically, a table view is created with a query (such as a SQL Select statement) so that the table view only contains a subset of the records from the physical table.

The Create Table View tool creates a table view from an input table. In contrast, the Create Query Table tool creates a table view from many input tables that can be linked.

If you want to save a table view in a physical table, use the Copy Rows tool.

Create a pivot table

You can use the Pivot Table tool to reduce redundancy in a large table. This is useful when converting certain CAD data structures to GIS features, as well as when converting a long list of measurement stations and values, separated by commas, into a table. Individual values ​​in a field (the pivot field) become column headings in the output table.

Grid tables

Often times, the pixel values ​​of rasters contain discontinuous integer values ​​that classify the data they contain, such as a type of vegetation. For example, a pixel value of 1 represents forest areas, while a pixel value of 2 represents swamp areas. For such rasters, it is a good idea to create a raster attribute table that describes each unique pixel value and that can be used to perform many of the table operations described above. You can use the Make Raster Attribute Table tool to create and update raster attribute tables.

Table tools

Dozens of tools are available for managing and editing tables and table attributes. Most of these tools are located in the Data Management toolbox.

Table operations

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