Author: Hannah Fry

So it turns out the internet is awesome.

After I posted a python script that can be used to convert a .csv of
Northings and Eastings in British National Grid to a Latitude and
Longitude, several people followed suit and sent through their codes in a
variety of other languages. 

I’ve just changed over my website and didn’t want to lose the codes, so
I’ve put them all here in one handy place. Hope you find them useful.

So it turns out the internet is awesome.

After I posted a python script that can be used to convert a .csv of
Northings and Eastings in British National Grid to a Latitude and
Longitude, several people followed suit and sent through their codes in a
variety of other languages. 

I’ve just changed over my website and didn’t want to lose the codes, so
I’ve put them all here in one handy place. Hope you find them useful.

This code reads in a .csv file called LatLon, expecting two columns with
headers – Latitude and Longitude (in WGS84, decimal form). If the script is
run in the same directory as LatLon.csv, it will spit out a second file
called LatLonandBNG.csv, with two additional columns: OSGB36 Eastings and
Northings respectively.

For the inverse transform – OSGB36 to WGS84 – please refer to this post,
where a you can find the relevant python script, and more details on the
algorithms involved.

If you don’t have python, you can find instructions for the bits you need
on another of my previous posts.

This code reads in a .csv file called LatLon, expecting two columns with
headers – Latitude and Longitude (in WGS84, decimal form). If the script is
run in the same directory as LatLon.csv, it will spit out a second file
called LatLonandBNG.csv, with two additional columns: OSGB36 Eastings and
Northings respectively.

For the inverse transform – OSGB36 to WGS84 – please refer to this post,
where a you can find the relevant python script, and more details on the
algorithms involved.

If you don’t have python, you can find instructions for the bits you need
on another of my previous posts.

A few months ago, I wrote a python script to convert British National grid
coordinates (OSGB36) to latitude and longitude (WGS84).  A fellow blogger
Andrzej Bieniek very kindly pointed out that the algorithm was only
accurate to around 100m because of an additional subtlety which I hadn’t
taken into account.

I’ll have a quick bash at explaining the reasoning behind this difference,
 but if you want to skip to the new version of the code (now accurate to
5m) I’ve posted it at the bottom of the page in all its delicious glory.
Alternatively, if you are looking for a similarly accurate script applying
the inverse transform – ie. WGS84 lat, lon to OSGB36 Eastings, Northings –
you can find it here.

A few months ago, I wrote a python script to convert British National grid
coordinates (OSGB36) to latitude and longitude (WGS84).  A fellow blogger
Andrzej Bieniek very kindly pointed out that the algorithm was only
accurate to around 100m because of an additional subtlety which I hadn’t
taken into account.

I’ll have a quick bash at explaining the reasoning behind this difference,
 but if you want to skip to the new version of the code (now accurate to
5m) I’ve posted it at the bottom of the page in all its delicious glory.
Alternatively, if you are looking for a similarly accurate script applying
the inverse transform – ie. WGS84 lat, lon to OSGB36 Eastings, Northings –
you can find it here.

EDIT: Andrzej Bieniek brought to my attention that this version is correct
to 100m. For a more accurate script (accurate to 5m) see my new post.

I have recently started to deal with a lot of geographical data in my
research and and begun to realise it is difficult to go to long without
stumbling across the sticky world of map projections – something I knew
almost nothing about a year ago.

There is a nice blog post explaining the background by James Cheshire
 which I shan’t attempt to reproduce, but explanations aside, I found
myself today trying to convert a long list of British National grid
coordinates into Latitude and Longitude.

EDIT: Andrzej Bieniek brought to my attention that this version is correct
to 100m. For a more accurate script (accurate to 5m) see my new post.

I have recently started to deal with a lot of geographical data in my
research and and begun to realise it is difficult to go to long without
stumbling across the sticky world of map projections – something I knew
almost nothing about a year ago.

There is a nice blog post explaining the background by James Cheshire
 which I shan’t attempt to reproduce, but explanations aside, I found
myself today trying to convert a long list of British National grid
coordinates into Latitude and Longitude.

This week: Bezier curves, how to draw them in Python and particularly, how
to decide where to put the control points.

A Bezier curve, is a special type of parametric curve used frequently in
computer graphics. You may have seen them in Powerpoint, or using the pen
tool in illustrator, but for my purpose, they are a lovely way to visualise
flow paths on a map, like this:

This week: Bezier curves, how to draw them in Python and particularly, how
to decide where to put the control points.

A Bezier curve, is a special type of parametric curve used frequently in
computer graphics. You may have seen them in Powerpoint, or using the pen
tool in illustrator, but for my purpose, they are a lovely way to visualise
flow paths on a map, like this: