npemap-talk December 2007

npemap-talk@lists.urchin.earth.li

5 participants
3 discussions

Marking / flagging incorrect entries
by russellallen 15 Dec '07

15 Dec '07

Hi all, I've recently found myself doing the same exercise as another poster on this thread to find potentially bogus entries - averaging postcodes per region and finding ones that are significantly outside where they belong. This raises a question though, let's say I believe these codes are suspect and so does everyone else (indeed I've checked one or two on other websites which use more "official" postcode data), should these codes be removed or at least marked somehow as bogus? If I'm going to use this data in a project of my own I could remove these entries having manually checked them, but then the data correction isn't being done in a shared way along with the data collection. What's the best way of setting a feedback mechanism like this up? If necessary I don't mind helping out? Russ -- View this message in context: http://www.nabble.com/Marking---flagging-incorrect-entries-tp14233507s26798… Sent from the NPEmap - Talk mailing list archive at Nabble.com.

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Std Dev - Finding Incorrect Entries
by Grant Slater 04 Dec '07

04 Dec '07

npemap, I have compiled a list of entries which vary greatly from their outbound's standard deviation: (worst entries at the top) http://code.firefishy.com/files/bad-postcodes.csv I am no statistician. Please correct me if I am off the mark. / Grant ------------------------ SQL: SELECT `postcodes`.`outward`, `postcodes`.`inward`, `postcodes`.`lat`, `postcodes`.`long`,`outbound_stats`.*, abs(`postcodes`.`lat`-`outbound_stats`.`lat_avg`) AS `lat_offset`, abs(`postcodes`.`long`-`outbound_stats`.`long_avg`) AS `long_offset` FROM `postcodes` LEFT JOIN `outbound_stats` ON `postcodes`.`outward` = `outbound_stats`.`outward` WHERE `outbound_stats`.`number` >= 10 AND ( (abs(`postcodes`.`lat`-`outbound_stats`.`lat_avg`) + abs(`postcodes`.`long`-`outbound_stats`.`long_avg`)) > (`outbound_stats`.`lat_stddev`*3 + `outbound_stats`.`long_stddev`*3 )) ORDER BY (`lat_offset`+`lat_offset`) DESC

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checking for bad postcodes
by markdc 03 Dec '07

03 Dec '07

You may have noted a spate of bad code reports north of Brighton from me last evening. As a new postcode mapper of - oh, about 3 minutes - I've been checking the data by using the postcode map at free the postcode: http://dev.openstreetmap.org/~random/postcodes/ This uses the npe codes as well as free the postcode codes to produce a postcode map at, for exapmle, BN1 level. Bad codes show as unlikely or even crazy post code zones on the map. For example, islands of BN1 in BN5 zones and even of SP1 in BN. These seem to be bad postcodes on the NPEmap and I've reported them. Probably a well known method but useful. let me know if there is anything I can do. Best wishes Mark -- View this message in context: http://www.nabble.com/checking-for-bad-postcodes-tf4930997s26798.html#a1411… Sent from the NPEmap - Talk mailing list archive at Nabble.com.

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npemap-talk December 2007