Adding Colored Regions to Excel Charts

Time series data is easy to display as a line chart, but drawing an interesting story out of the data may be difficult without additional description or clever labeling. One option, however, is to add regions to your time series charts to indicate historical periods or visualization binary data.

Here is an example where a chart of annual U.S. national economic indicators has been enhanced with regions that also indicate contractions in the U.S. business cycle – roughly speaking, economic recessions.

A time series with colored regions in the background, created in Excel.

To create this chart, all of the indicators were averaged by year and, where necessary, adjusted for inflation using a conversion factor. Download the time series data Excel file for the data and the chart to follow along.

First, to set up the basic line chart, hold Ctrl (PC) or Cmd (Mac) while you select the following columns:

  • D (stock price index over CF…)
  • E (avg. annual unemployment…)
  • G (GDP over CF…)
  • I (debt over CF…)
  • K (interest rate * 10)
  • L (years economy is in decline)

Youll notice that the columns are color coded. Some colors apply to multiple columns; this is because the values that appear on the chart have been calculated by transforming the raw data in some way. Each line on the final chart thus corresponds to one or more columns of data used to produce the values. Transforming the values helps us by normalizing the values (i.e., adjusting for inflation) or scaling the data series itself (making it possible to see the relationships between many different indicators on a single graph, despite wide variations in the ranges of values).

When we select the six columns above and insert a line chart, we get a rather ugly line chart.

The chart as it looks with the default Excel settings.

We’ll make several changes to improve this:

  • Change the “years… in decline” series to an area chart
  • Select and adjust the x axis labels and ticks
  • Adjust the y axis range
  • Customize the color, label, and order of the data series

The basic mechanism of the colored regions on the chart is to use Excel’s “area chart” to create rectangular areas. The area chart essentially takes a line chart and fills the area under the line with a color. If we have a continuous horizontal line as a data series, we will create a large colored rectangle on the chart. To have breaks in the rectangle, we simply need to leave some of the years blank (without values in the cells). To select the appropriate values for column L, we first found the maximum value for the other data series and determined that a value of 20 would create bars starting above the other data series.

To produce the colored regions that indicate contractions in the business cycle, we take the series that was created from column L and turn it into an area chart.

  1. Right-click on any data point in the series or on the legend entry
  2. Select “Change Series Chart Type…”
    Changing the chart type for a particular data series.
  3. Select the standard Area chart from the ribbon
    Select Area from the ribbon.

The chart now fills in the area under the original lines with a default fill color.

After changing one series to an Area chart.

At this point, you can right click on the series again, select “Format Data Series…”, and change the Fill color to a light gray.

Changing the fill color of the Area series.

Next, we tell the x axis what the correct labels are (the “Year” column) and have the labels show up every 4 years. (Our data series start on an election year, so the labels will always appear on election years.)

      1. Right click inside the chart somewhere and select “Select Data…”
      2. Select any of the data series in the “Series” list, then go over to the “Category (X) axis labels” box and select the “Year” column. Click “OK”.
        Changing the X axis labels.
      3. Right-click on the x axis and select “Format Axis…”.
      4. Under “Scale”:
        1. Change the default interval between labels from 3 to 4
        2. Change the interval between tick marks to 4 as well
        3. Uncheck the box next to “Vertical axis crosses between categories”
          Changing the X axis scale.
      5. Under “Text Box”, select the text direction of “Rotate to 90 deg Counterclockwise”. Click “OK”.
        Changing the X axis text.

The x axis should have appropriate year labels now. The y axis can similarly be adjusted to show just the range of values we’re most interested in.

      1. Right-click on the axis and select “Format Axis…”.
      2. Under “Scale”, unselect the check box next to “Maximum:” and change the value to 20.
        Changing the Y axis scale.

The rest of the changes are simply formatting changes. Right-click on the individual data series to change the colors, line widths, etc. Use the formatting options or the Chart tools on the Excel ribbon to change the font of any text, adjust the grid lines, add labels and titles, etc. The data series names in the legend can be adjusted by using the “Select Data…” option and typing in custom text in the “Name” field.

The final product should have colored regions and look something like the chart below.

A time series with colored regions in the background, created in Excel.

In another post, we will show how to spice this chart up even more using Adobe Illustrator.

Data and GIS Back to School – Fall 2012

Visualize your data, analyze your results, map your statistics, and find the data you need!  Come visit us in Perkins 226 (second floor Perkins) for a consultation or contact us online (email: askdata@duke.edu or twitter: duke_data OR duke_vis).  We look forward to working with you on your next data driven project.

New Data Lab Opens- August 2012

http://library.duke.edu/data/about/lab.html

With 12 workstations with dual 24″ monitors and 16 gigs of memory, the new Data and GIS lab is ready to take on the most challenging statistical, mapping, and visualization research projects.  The new lab also features a flatbed scanner for projects moving from print to digital data.  Lab hours are the same hours as Perkins Library (almost 24/7).

Visualize This!  New Data Visualization Program

Perkins Library is proud to introduce Angela Zoss our new Data Visualization Coordinator. Schedule a consultation, attend a workshop, or learn more about research in Data Visualization at Viz Forum this fall.

New workshops for Fall 2012

http://library.duke.edu/data/news/index.html

Learn about data management planning. Apply text mining strategies to understand your documents.  Visualize your data with Tableau Public, or map your results using ArcGIS or Google Earth Pro.  A new series of workshops connects traditional statistical, geospatial, and visualization tools with web based options.  Register online for our courses or schedule a session for your course by emailing askdata@duke.edu

Bloomberg Professional News and Financial Data

http://blogs.library.duke.edu/data/2011/08/29/bloomberg-has-arrived/

If you missed last fall’s Bloomberg service – Duke Libraries in pleased to announce the installation of three Bloomberg financial terminals in the Data and GIS Lab in 226 Perkins.  The terminals provide the latest news and financial data and include an application that makes it easy to export data to Excel.  Access is restricted to all current Duke affiliates.  Training on Bloomberg is currently being planned for the last week of September.  Please email askdata@duke.edu to reserve a space at the training session.

Get help with Data Management Planning

http://library.duke.edu/data/guides/data-management/index.html

Data and GIS has launched a new guide that provides guidance for researchers looking for advice on data management plans now required by several granting agencies.  The guide provides examples of sample plans, key concepts involved in writing a plan, and contact information for groups on campus providing data management advice.  In addition, we offer individual consultations with researchers on data management planning.

New Collections for Fall 2012

http://library.duke.edu/data/collections/new.html

Contact Us! – askdata@duke.edu

 

Online Mapping Tools – GeoCommons

Visualizing spatial data can be challenging.  Specialized software tools like ArcGIS produce excellent results, but often seem complex for relatively simple tasks. Several online tools have emerged recently that provide relatively easy alternatives for the display of spatial data.  In this post, we examine GeoCommons, a web based tool for presenting spatial data in detail.  (Go to this guide to see a comparison chart of packages and features, and see this Duke University Libguide for a more detailed review of GeoCommons.)

 

GeoCommons (geocommons.com)

GeoCommons is an online mapping application that easily imports a variety of data formats, including geospatial data, and quickly produces sharable maps.  In contrast to other mapping tools, GeoCommons contains several categorization algorithms, such as quantile classification and classification based on the standard deviation of the sample that assist with the construction of informative maps.  CSV files and ArcGIS shapefiles are two of the most widely used file formats compatible with GeoCommons.

GeoCommons is very easy to use and contains some of the display features contained in high-end GIS suites.  Creation of new variables tied to geographies can be tricky, so it’s advised to either upload data  and map in final form or to first identify the layer to which you will upload and join a complete data set.

 

Geocoding

Figure 1

To begin geocoding, upload a file.  Gecommons has the capability to recognize spatially encoded data.  Some formats may require user assistance.

If you’ve uploaded data that contains latitude and longitude coordinates, choose this option.  In my case, I had county FIPS codes that uniquely identified each county.  Selecting US Boundaries to the left, then USA Counties, I was able to successfully preview how well my FIPS codes matched the layer (Figures 1 and 2).  A variety of other boundary types are available.  The key is to have in your data a unique identifier that identifies each record in the same manner as an available geocoding layer.

Figure 2

Review the geocoding results and select Continue to proceed.

 

Mapping

Geocommons offers some nice built in features that assist with categorizing measures.  The application will produce summary statistics for numeric fields (Figure 3), which gives you a quick picture of your sample and can assist with how to categorize the data.  Click the “Make a Map” button to proceed to the interactive interface.

Figure 3

Also note the filter tab, which allows you to screen out groups of cases.  For example, I may request a minimum number of farms to screen out urban counties.

Figure 4 shows a standard choropleth map portraying median number of acres per farm by county for North Carolina in 2007.  In this example, I have classified counties into five groups using standard deviations to group counties.

 

Sharing

Figure 4

GeoCommons contains a wide variety of ways to share data (accessed through the About section).  Posting to Twitter, Facebook, and an array of other social media sites is possible with a few short clicks.  You can directly email a link to the map along with a short personal message right out of the application.For those who wish to post to a web page, GeoCommons provides two ways to insert a map, through a <div> tag and through an iframe.  All code is generated for copy and paste into your page.

To access a version of this map, simply follow this link.

Finally, GeoCommons will produce a PNG image and a KML document for download.  The image export feature appears to be relatively new and does take trial-and-error to align correctly.  In addition, it does not appear to include any base layers or legends in the output, only the data layer.

 

Other Notes

When using standard deviation and maximum breaks methods for grouping observations, double check the category definitions by changing the number of categories and the resulting changes to the definitions for the new groups.  This will help to confirm whether data are grouped appropriately and exactly what the definitions for each category are.

New Data Visualization Services at Data and GIS

Data visualization has a long history, but disciplines employ visualization for different purposes and with varying levels of complexity.  Visualizations can be compelling or confusing, engaging or enraging.  For researchers without prior experience with visualization, the cost of incorporating new techniques into an existing research program may be daunting.

A stacked area graph.

The Data & GIS Services Department of Perkins Library can help with data visualization at various scales and in any discipline.  Angela Zoss, Duke’s new full-time Data Visualization Coordinator, has arrived and is available for consultation.  Her role will be to provide visualization support for the Duke University community and to help centralize visualization resources and infrastructure.

A U.S. map with a data overlay of circular icons.

In addition to the existing mapping services and visualization workshops that have been offered for some time, this fall will bring new visualization workshops, instructional material, and web resources to assist with various components of the research process (e.g., data processing and analysis, software selection, post production).  Look for information not only on producing visualizations but also on opportunities for showcasing visualizations and research across campus. Our new visualization twitter feed (@duke_vis) will also be used to circulate tutorials, example visualizations, and other news and events related to visualization.

A network visualization.

There is no better time to start exploring what visualization can offer!  Stop by Perkins during our walk-in hours or send an email to askdata@duke.edu for consultation, or get in touch with Angela directly to learn more about the new visualization services.

Online Mapping Tools – Tableau Public 7

Visualizing spatial data can be challenging to learn. Specialized software tools like ArcGIS produce excellent results, but often seem complex for relatively simple tasks. Several online tools have emerged recently and provide relatively easy alternatives for the display of spatial data. In this ongoing series of alternatives, we review Tableau Public 7 in detail.  Go to this guide to see a comparison chart of packages and features, and see this Duke University Libguide for a more detailed review of Tableau 6.1.

 

Tableau Public (link)

Figure 1

Tableau Public is a free software application that allows you to easily map data and share maps through email or web pages by embeddable script. To use Tableau, you must download and install a free desktop application. Tableau Public also requires a free registration to share visualizations created in the software.

Tableau is designed to look and feel like a standard spreadsheet application. Geographic mapping is accomplished by dragging your coordinate fields and dropping them into the columns and rows fields (see Figure 1). In Tableau 7, you may also select “Filled Map” under the Marks panel, and select a geographic identifier for the “Level of Detail” field (see Figure 2). Once done, add the variable to color by to the color field. In these examples, more intense colors indicate larger median farm size, measured in acres.

Figure 2

 

Geocoding

Tableau generates new fields that hold coordinate data as it imports and geocodes your data. If you wish to create filled maps (states, counties, etc.) in Tableau 7, you must additionally have geographic identifiers that are unique for each case. In Figure 2, the initial map only contained 50 polygons, as 50 North Carolina counties were uniquely named within the United States.

Had I also included a state field, unique identification would have been automatic, but Tableau allowed me to define the state for each case, and lucky for me, I only had North Carolina data.

The geocoding options are extensive. The following list is not exhaustive: area codes, FIPS codes, county/state/country names, ZIP codes, and ISO country codes. Of course, any coordinate data will work for point data.

 

Sharing

Sharing on a web page is accomplished through embeddable Javascript. Sadly, I was unable to get Tableau to work within WordPress, but you may see a live version of this map by following this link.

 

Other Notes

Tableau is very easy to use, provided your data is reasonably clean. With geographic data, be certain to either have something that uniquely identifies each entity or have latitudes and longitudes. It is preferable to err on the side of including more identification fields rather than less (i.e. including state names in addition to counties).

Also be aware that Tableau is not backward-compatible. For example, the workbook used in this example was initially created in Tableau 6.1, modified in Tableau 7, but failed to open once I moved back to Tableau 6.1. However, irrespective of version, you will be able to see any visualizations produced in any version.

 

ACS Mapping Extension for ArcGIS

The Census Bureau’s American Community Survey provides a continuous measure of the community demographics in the US.   A  new extension provided by the Department of Geography and Geoinformation Science at Geroge Mason University enhances the mapping of ACS by data by allowing researchers to visualize both survey estimates while revealing the level of uncertainty in the estimates.  ACS Mapping Extensions is an ArcGIS addon available for both ArcGIS 9.3 and 10.  This post provides a brief overview of installation, setup, and use.  Detailed technical assistance is provided by the extension.

 

 

Installation
1) Once you download the program, you will want to install and note the installation directory.  In ArcGIS, select Customize from the menu bar, and click Customize Mode….  Then select “Add from file…” and navigate to the installation directory.  Once in this directory, select the “ACSMapping.tlb” file.

 

2) Before you leave the Customize window, be sure to check the “ACS Mapping Tools” toolbar.  You will have a new “ACS Mapping” toolbar added to your window.

 

 

Setup
1) The “Documentation” option in the “ACS Mapping” toolbar provides detailed instructions for downloading ACS data and boundary files.  Follow these instructions to the letter and to their entirety.  With respect to boundary files, the TIGER 2008 county boundaries were used for this example.

 

2) Add the boundary layer to a blank map and select “Join ACS Table(s) with Shapefiles” option in the “ACS Mapping” toolbar.  In this example, I have downloaded county boundaries and county-level median income data from the 2005-09 ACS.  In this figure, the first two fields indicate the items to be joined, one table to one shapefile.   “CNTYIDFP” represents the FIPS code in the boundary file, and “GEO_ID2” is the corresponding code in the ACS table.  Once you’ve set an output location, select “OK.”

 

3) Finally, you will want to apply a symbology to the layer.  In this case, I chose the median income estimate and 5 total categories.  The following figure shows what my map looks like at this point.

 

 

Mapping ACS Estimates with Coefficients of Variation

1) The tools are located under the “Mapping Data Uncertainty” option in the ACS Mapping toolbar.  The first option, “Overlay CVs with Estimates,” will allow you to visualize the uncertainty of estimates at the same time as the estimates themselves.    As noted by the documetation provided by the ACS Mapping Extension web site, ACS provides a margin of error that produces a confidence level of 90%.  This tool will convert these data into coefficients of variation that will allow you to assess the quality of the estimates.

 

2) Select the target layer to whcih you added symbology, select the variable that stores the estimate to be calculated, and finally, select the variable that stores the margin of error (suffix = “_M”).

 

3) After you click the “Select” button, you will be presented with the new Symbology options for the new coefficients of variation layer to be generated.  In this case, I retained the automatic selections and hit “OK.”

 

4) Zooming in to central North Carolina, one can see not only that the Research Triangle Area has relatively high incomes compared with much of North Carolina, but that coefficients of variation are lower than thay are for parts of northern North Carolina and southern Virginia.

 

 

Measuring Singificant Differences in Income
1) The second option, “Identify Areas of Significant Differences,” allows you to assess whether there is a significant difference between one spatial unit and all other spatial units for a given variable.  In order for this option to work, you must select one specific spatial unit.  In this example, I selected Durham County and will assess whether there are significant differences in median household income in the region.

 

2) First, select the target layer for which you selected a single feature.  You want to verify the estimates and margin of error variables, and you can adjust the confidence level from the default 90%.  Select OK.

 

3) The output is represented by four different symbologies.  First, your chosen county is filled with dots.  All counties that are significantly different are striped, while all those that are not are empty.  Finally, when significance cannot be determined, the original color fill is replaced with a new color.  In this case, median household income is not significantly different between Durham and Chatham counties.  However, this could be due to small differences or large margins of error in one or both counties.

 

 

Data and GIS Winter Newsletter 2012

Data driven teaching and research at Duke keeps growing and Perkins Data and GIS continues to increase support for researchers and classes employing data, GIS, and data visualization tools.  Whether your discipline is in the Humanities, Sciences, or Social Sciences, Perkins Data and GIS seeks to support researchers and students using numeric and geospatial data across the disciplines.

New Website for 2012
http://library.duke.edu/data/

You can find:

  • Online data or digital maps that you need for your project
  • A workshop on the latest software packages and digital tools

New workshops for 2012
http://library.duke.edu/data/news/index.html
Clean your data with Google Refine. Learn about data management planning. Visualize your data with Tableau Public, or map your results using ArcGIS or Google Earth Pro.  A new series of workshops connects traditional statistical, geospatial, and visualization tools with web based options.  Register online for our courses or schedule a session for your course by emailing askdata@duke.edu

  • StataReview                               (Statistics/Data Management)
  • Introduction to ArcGIS           (Geographic Information Systems / Data Visualization)
  • Data Management Planning  (Data Management/Grants)
  • Geocommons                            (Geographic Information Systems / Data Visualization)
  • Google Earth (Pro)                   (Geographic Information Systems / Data Visualization)
  • Google Refine                           (Data Management/Descriptive Statistics)
  • Tableau Public                          (Data Visualization)

Bloomberg (terminals) have arrived
http://blogs.library.duke.edu/data/2011/08/29/bloomberg-has-arrived/

Duke Libraries in pleased to announce the installation of three Bloomberg financial terminals in the Data and GIS Lab in 226 Perkins.  The terminals provide the latest news and financial data and include an application that makes it easy to export data to Excel.  Access is restricted to all current Duke affiliates.

Get help with Data Management Planning
http://library.duke.edu/data/guides/data-management/index.html

Data and GIS has launched a new guide that provides guidance for researchers looking for advice on data management plans now required by several granting agencies.  The guide provides examples of sample plans, key concepts involved in writing a plan, and contact information for groups on campus providing data management advice.

New Collections
http://library.duke.edu/data/collections/new.html
Explore the Indonesian Village Potential Statistics (PODES), look at household economic behavior in the Indian National Sample Survey, or explore historical digital maps of Europe- the Data and GIS collection collects research data sets and maps of interest to the Duke community covering a wide range of topics.

Support for Restricted Data Contracts and Restricted Data Licensing
Perkins Library has partnered with the Social Science Research Institute (SSRI) to support restricted data licensing with Paul Pooley as a restricted data specialist.  Paul is available  to work with researchers licensing restricted data and negotiating restricted data management plans.  Please contact Paul paul.pooley@duke.edu or askdata@duke.edu for more details.

Contact Us!askdata@duke.edu – twitter: duke_datahttp://library.duke.edu/data/hours.html

Joel Herndon
Head, Data and GIS Services
919-660-5946
Location: Room 227 Perkins
joel.herndon@duke.edu
Mark Thomas
Economics/GIS Librarian
919-660-5853
Location: Room 233 Perkins
mark.thomas@duke.edu
Teddy Gray
Biological Sciences Librarian
919-660-5971
Location: Room 233 Perkins
teddy.gray@duke.edu

ArcGIS Tutorial – Georeferencing Imagery

One of the limitations of computer mapping technology is that it is new. There is little historical imagery and data available as a result, although this has started to change. The integration of paper and imaged maps into computer mapping technology is possible, and this tutorial will walk through the process of georeferencing.

Georeferencing is the process of placing an image into two dimensional space. In essence, georeferencing pins a scanned map to particular geographical coordinates.

This tutorial will georeference a map of Durham County from 1955. In addition to the scanned map, we will use two current layers as referents: the Durham roads layer, and the Durham county boundary. Note that because the layers are more recent than the historical map, many roads will not exist in the image. Georeferencing historical imagery requires familiarity with geographic characteristics and changes.

 

Step 1: Enable Georeferencing

First, under the “Customize” Menu Bar option, navigate to “Toolbar” and select Georeferencing. The figure to the right displays the Georeferencing toolbar.

 

Step 2: Add Data and Image Layers

Next, add the shapefiles that you will use as referents for the image.

Once this is done, add the image to be georeferenced.  Note that you will almost certainly not see that image, as it lacks spatial coordinates. However, the image will appear in the Table of Contents.

In this example, I have added Durham County (blue polygon) and the Durham roads layer (blue lines).

 

Step 3: Fitting the Image to the Layers

The next step will relocate the image to the center of your current window and will expand the image only to the point where the entire image is visible. In this case, Durham County is taller than it is wide, so vertical space will be maximized.

First, it is a good idea to zoom, if necessary, so that your current view roughly matches where the image will be place. In this case, zooming to the full extent of the Durham county boundary will accomplish this.

Second, under the Georeferencing toolbar, click “Georeferencing” and select “Fit to Display.” The image should be roughly aligned to the data layers, though if not, this is not problematic.

As you can see from the image to the right, there is some distance between the county boundaries of today (red lines) to the hand-drawn county boundaries located in the image (white lines).

 

Step 4: Adjusting the Map

ArcGIS georeferences images through the addition of control points. The control points tool (to the right) operates through two mouse clicks: the first mouse click selects a point on the image, and the second mouse click pins that point to a location within a data layer.

For example, in the image to the right, I have selected a major intersection that likely has not changed in the last 60 years. After my first click, where I’ve selected a point near the top of the intersection, a green crosshair is placed. As I move the mouse, ArcGIS will pin my current crosshair to a proximate layer, in this case, the Durham roads layer.

Once you click a second time, the map will move to conform to the new control points. Control points work in combination, so as you add new control points, your image will (ideally) match more closely to your referents.

There is a limit to how much each subsequent control point will improve fit as more points are added. Generally, it’s a good idea to zoom in to improve accuracy and to create control points across the extent of the image.

After about 15 control points, we can compare the image to the included shapefiles. As you can see, if we assume that major roads have not changed, the green lines correspond well to the image, while the county boundary does to a lesser extent.

 

Step 5: Statistics and Transformations

Before saving the results, it is also a good idea to evaluate the results. Open the Table of Points to see each of your control points and the root mean squared error of all control points.

The Root Mean Square error (RMS) provides a rough guide to how consistent your control points are to one another with reference to the map.  Note that a low value does not mean that you’ve necessarily georeferenced the image well, it means you’ve georeferenced consistently.  High RMS errors indicate that your control points are less consistent with one another in comparison with a low RMS error.  One way to address this issue is to identify especially probelmatic control points and either replace or remove these points.  However, always reevaluate how well your image maps to the referent shapefiles.

You may delete control points or add new points at this stage. In addition, you may also try different transformations, although second- or third-order transformations are rarely needed.

 

Step 6: Saving the Results

Under the Georeferencing tab of the Georeferencing toolbar, select “Update Georeferencing.” Spatial information is saved in two new files that MUST accompany the image, an “.aux” file and a “.thw” file.

 

General Tips

– Zoom close to the layer resolution in order to improve accuracy

– Use more than 1 referent if possible. In this example, the county boundary provided a rough guide with respect to how far off the image initially is, but was not used to actually georeference the image.

– Georeference to accurate features. In this example, the county boundary was hand-drawn on the image and is not as precise as photographed features, like roads.

What’s new in ArcGIS 10?

Basemaps

Would you like to add aerial photography or a topographic map underneath map layers for visual appeal or context? With ArcGIS 10, you can add a basemap to your map project.

A basemap is a link to an online imagery data source. You must be connected to the Internet in order to see a basemap.

Basemaps contain imagery at different levels of detail. When zooming in or out, new imagery will replace old imagery, which provides an approprate level of detail at any zoom level and improves performance by limiting the amount of information to be downloaded and displayed.

 

Export Map Packages

Sharing maps and shapefiles with others can be a pain when a map is composed of many shapefiles and layers.  A map package bundles all shapefiles, layers, and map documents into a single file that can be opened by others with ArcGIS 10.

 

Background Processing

In ArcGIS 10, ArcToolbox tools default to background processing.  This allows you to continue to work while the tool processes your data.

To disable background processing, navigate to the “Geoprocessing Options…” choice under the Geoprocessing Menu Bar, and uncheck the “Enable” box.

 

Search Toolbox Feature

Got a tool you want to use but can’t remember what toolbox its in?  With the Search feature, you can easily locate what you need. Your search term can be the tool name or a close approximation of what you wish to do.

 

Easy to Use Time Data

Time series data became easier to use with ArcGIS 10. Version 10 recognizes time series data with the addition of a single time field.

For example, suppose you have annual precipitation for US cities.  Your data will contain an ID field, a point field, a time field containing the year, and a field containing the precipitation amount.

For more information, see this blog post.

 

How Do I Label Individual Items?

Have you ever wanted to label individudal items on a map, and avoid the cluttered appearance of labels for all features, such as that shown to the right?

ArcGIS 10 hides the tool that you use to label individual items, but it’s easy to get back.

  1. Turn on the “Labeling” toolbar under the Customize Menu Bar.
  2. At the top right corner of the toolbar, click the arrow pointed downward and click “Customize…”
  3. Select the “Commands” tab and select the “Label” category (left panel).
  4. In the right panel, drag the “Label” tool and drop it into any toolbar that you wish.

Converting ArcGIS Layers to Google Earth (KML)

Converting ArcGIS layers to Google Earth allows others to easily see layers without specialized software.  Both ArcGIS and Google Earth Pro contain tools that allow conversion to and saving in KML format.
Note: Be certain you are allowed to share layers if they were not created by you.

Conversion using ArcGIS

  • First, open the layer that you wish to covert.
  • In the ArcToolbox window, expand “Conversion Tools,” then “To KML,” and select “Layer to KML.”
  • When the “Layer to KML” window appears, first select the shapefile or layer for the “Layer” box.
  • Next select a directory for the file to be created and provide a name for the file.
  • Finally, you must enter a number for the “Layer Output Scale.”  If your layer has a scale-dependent renderer, this setting allows you to export the KML at a specific level of resolution.  Otherwise, it has no effect, whatever the number.

For layers with many features, ArcGIS may produce a KML file that does not open in Google Earth due to errors.  There are two ways to solve this problem.

  • First, you can split your shapefile into several smaller shaepfiles.
  • Second, you can (usually) convert the shapefile to KML with Google Earth Pro.

Conversion using Google Earth Pro

  • First, open the shapefile with the Open command.  Be certain to change the file type to “ESRI Shapefile”.
  • When opened, you will receive a warning if your shapefile contains more than 2,500 items.  You will still possess the ability to import the entire file, but it may take some time.
  • You will be asked whether you wish to apply a style template to the document.  If you do so, you will be able to choose the attribute that contains the item name (for example, the address field or the street name field).
    Note: you don’t have to save the style template to select the name field.
  • Finally, right-click the layer added to the Temporary Places folder, and click “Save Place As.”  Provide a location and file name for the file to be created.