Find your perfect home with Google Fusion Tables

My husband and I were recently in the market for a new home. We worked with a realtor for a few months, looking at several houses every weekend. As we checked out each house, we tracked our thoughts about it in a Google spreadsheet, which included columns for the address, our pros and cons, individual ratings and the combined rating of the house.

One day, while my husband and I were rating a recently viewed home, he came up with a brilliant idea to put all of our home data on a map. We realized that adding geographic information to our personal opinions would help us find trends, such as which neighborhoods we preferred. A light bulb went on over my head: Google Fusion Tables!

Fusion Tables is a data management web application that makes it easy to view tabular data on a Google Map. Columns with location data, such as addresses, points, lines, or polygons, are automatically interpreted and mapped. The map features can be styled according to the data in your table. It’s also simple to share the map visualization with others.

In just a few steps, we were able to convert our spreadsheet into a fusion table:

This was a great start, but what we really wanted was to quickly get a glimpse of this data on a map. All we had to do was select ‘Visualize > Map’ from the table menu and the data in the ‘Address’ column was geocoded (i.e. converted into latitude and longitude coordinates) and the markers were displayed on the map. Clicking on the markers showed additional information about the house pulled from our spreadsheet, including the pros, cons and ratings we inputted for each location.

Our house ratings viewed in Google Maps (after being converted into a Fusion Table).
Fusion Tables also allow you to style the features on the map according to data in a numerical column in the table. We had the perfect column to use for this purpose: the ‘Total Rating’ column!


In order to color code the map markers by their ‘Total Rating’ score, we customized the icons based on a range of scores, with red representing the lowest scores, yellow show mid-range scores and green showing the houses with the highest combined rating. After saving these new settings, the map markers were immediately styled:

Our new map made it much easier to see what locations we were most interested in (the house just south of Redwood City) and the neighborhoods of low interest (those that were closer to the bay or hills).

We shared the map with our realtor and she loved it. It helped her refine the selection of homes she showed us and in just a matter of weeks, I’m happy to say that my husband and I found the perfect house!

Posted by Kathryn Hurley, Developer Programs Engineer, Geo DevRel

via: GoogleLatlong

How to make maps with Fusion Tables

Inspired by the Guardian Data Blog I decided to explore Fusion Tables and Google Maps with Australian data. To start with, I selected a set of Socio-Economic Indexes for Areas, created from 2006 Census data, and postal area boundaries from the Australian Bureau of Statistics (ABS).Today I would like to share a few observations regarding creating maps with data from Fusion Tables.

Although Fusion Tables is not yet a fully featured thematic mapping, analysis and publishing application however, with a little bit of effort, anyone can create informative maps which are visually attractive and fast to deploy. The best thing about Fusion Tables is that you don’t need to manage any complex infrastructure yourself and that the application is free (however, with some limitations on data storage volumes, currently capped at 250MB per account).

Spatial Data

Since Fusion Tables support spatial data only in KML format you have to convert your dataset before uploading it to the server, or alternatively, find a publicly available table that has already been uploaded by someone else.

Google provides a tool to translate SHP data into KML format and to import directly into Fusion Tables but it didn’t work for me with complex data. There are some free alternatives available (really easy to use one is QGIS, for example) but loading other than KML data into Fusion Tables will always be a multi step process.

If you decide to upload your own data, please note a couple of annoying limitations of Fusion Tables. Firstly, complex polygon structures are not supported (for example, I could not upload postcode number 0822 in Northern Territory at full resolution, yet it works perfectly with Google Maps). Secondly, some larger polygons and/or with many parts get generalised automatically as you load them to Fusion Tables as, for example, postal area 7255 in Tasmania (compare the results below – the same KML file as imported to Fusion Tables, on the left, and as displayed directly on Google Map – note green outlines on all, even the smallest islands):

Table search functionality in Fusion Tables is rather crude so, it may not be an easy task to locate what you are looking for. Not to mention that the concept of metadata is non-existent in Fusion Tables so, it is hard to know if the data you find is appropriate for your purposes.

Numeric data

Upload of tabular numeric information in csv format is very straightforward but if you disallow “Export” option up front, you will not be able to edit the data in Fusion Tables. My suggestion is to import the data as “Private” (default option) and allow for “Export”, then add new columns with formulas (if required), and disallow export only when you are ready to publish the data (if at all).

Table Operations

You can easily create a map based on data from numeric tables if those tables contain a “spatial reference” column, for example, postcode numbers (provided you can find equivalent spatial data set in Fusion Tables). To combine numeric and spatial data tables you have to use “Merge” function. My suggestion is to use “smaller table” as a starting point. For example, to create thematic map with postcodes for Sydney area only, select relevant numeric table first and then merge with a table containing postal areas for the entire NSW. Only relevant boundaries will be included in the merged table (ie. the subset of NSW postcodes). If you do the operation in the reverse order, the merged table will contain all postcodes for NSW but only a handful will have the data that can be used in creating a thematic map.

When you “Create View” (ie. copy the table – your own or from other users to your account) or “Merge” tables with spatial geometry column you will lose map formatting parameters (eg. colour setting for polygon fills, etc.). This is very unfortunate, especially when you need to retain colour schema from the original table.

Styling Map

Handling “No data” fields is not easy in Fusion Tables. The problem is that polygons with “no value” in the table default to red fill when rendered on the map (as in the example below – there was no data for 2006 postcode in the merged numeric table). A workaround is to include some value in the table for the missing record (eg. traditional -9999) if you can. Then you can specify map settings to colour only that value, for example, as white and/or fully transparent.

Fully transparent overlays (eg. if fill is set to 0% transparency) are not clickable – it is a very handy feature for handling polygons with missing data in the numeric table (ie. no information window will be displayed when the polygon is clicked). However, when your objective is to present on the map only outlines of the polygons but you still want to display information about those polygons on click of the map, you have to change transparency parameter to a value greater than 0.


If you are eager to start playing with Fusion Tables, Google produced easy to follow tutorial on how to create thematic maps (note, if you are working with your own data, choose “Map” option and not “Intensity Map” in the relevant step).

Examples for Exporting Access table or query to EXCEL Workbook Files Part 4

Create an Access Query and Export multiple “filtered” versions of an Access  Query (based on data in another table) to separate Worksheets within one EXCEL file via TransferSpreadsheet (VBA)

Generic code to create a temporary query, get list of filtering values, and then loop through the list to filter various data and export each filtered query to separate EXCEL files. In this sample code, the employees assigned to each manager are exported to separate worksheets within the same EXCEL file, one worksheet for each manager.

Dim qdf As DAO.QueryDef
Dim dbs As DAO.Database
Dim rstMgr As DAO.Recordset
Dim strSQL As String, strTemp As String, strMgr As String

' Replace PutEXCELFileNameHereWithoutdotxls with actual EXCEL
' filename without the .xls extension
' (for example, MyEXCELFileName, BUT NOT MyEXCELFileName.xls)
Const strFileName As String = "PutEXCELFileNameHereWithoutdotxls"

Const strQName As String = "zExportQuery"

Set dbs = CurrentDb

' Create temporary query that will be used for exporting data;
' we give it a dummy SQL statement initially (this name will
' be changed by the code to conform to each manager's identification)
strTemp = dbs.TableDefs(0).Name
strSQL = "SELECT * FROM [" & strTemp & "] WHERE 1=0;"
Set qdf = dbs.CreateQueryDef(strQName, strSQL)
strTemp = strQName

' *** code to set strSQL needs to be changed to conform to your
' *** database design -- ManagerID and EmployeesTable need to
' *** be changed to your table and field names
' Get list of ManagerID values -- note: replace my generic table and field names
' with the real names of the EmployeesTable table and the ManagerID field
strSQL = "SELECT DISTINCT ManagerID FROM EmployeesTable;"
Set rstMgr = dbs.OpenRecordset(strSQL, dbOpenDynaset, dbReadOnly)

' Now loop through list of ManagerID values and create a query for each ManagerID
' so that the data can be exported -- the code assumes that the actual names
' of the managers are in a lookup table -- again, replace generic names with
' real names of tables and fields
If rstMgr.EOF = False And rstMgr.BOF = False Then
Do While rstMgr.EOF = False

' *** code to set strMgr needs to be changed to conform to your
' *** database design -- ManagerNameField, ManagersTable, and
' *** ManagerID need to be changed to your table and field names
' *** be changed to your table and field names
strMgr = DLookup("ManagerNameField", "ManagersTable", _
"ManagerID = " & rstMgr!ManagerID.Value)

' *** code to set strSQL needs to be changed to conform to your
' *** database design -- ManagerID, EmployeesTable need to
' *** be changed to your table and field names
strSQL = "SELECT * FROM EmployeesTable WHERE " & _
"ManagerID = " & rstMgr!ManagerID.Value & ";"
Set qdf = dbs.QueryDefs(strTemp)
qdf.Name = "q_" & strMgr
strTemp = qdf.Name
qdf.SQL = strSQL
Set qdf = Nothing

' Replace C:\FolderName\ with actual path
DoCmd.TransferSpreadsheet acExport, acSpreadsheetTypeExcel9, _
strTemp, "C:\FolderName\" & strFileName & ".xls"
End If

Set rstMgr = Nothing

dbs.QueryDefs.Delete strTemp
Set dbs = Nothing