Usage:

from lat_lon_parser import parse

In [12]: from lat_lon_parser import parse

In [13]: parse("45° 12.6' W")
Out[13]: -45.21

Formats supported:

Decimal degrees (easy):

23.43
-45.21

Decimal Degrees with quadrant:

23.43 N
45.21 W

Or with spelled out:

23.43 North
45.21 West

(note that all of the cardinal directions are not case-sensitive)

Degrees, decimal minutes: (now it starts getting tricky!):

23° 25.800'
-45° 12.600'

or:

23 25.800'
-45 12.600'

or:

23° 25.8' N
45° 12.6' West

Degrees, Minutes, Seconds: (really fun!!!):

 23° 25' 48.0"
-45° 12' 36.0"

or:

 23d 25' 48.0"
-45d 12' 36.0"

or:

23° 25' 48.0" North
45° 12' 36.0" S

or – lots of other combinations!

For a more complete list, see the tests

How it works:

This uses a pretty “stupid” algorithm – it assumes that all formats will be something like:

[-][space] degrees [separator] minutes [separator] seconds [separator] [N[orth]|S[outh|E[ast]|W[est]]

But that actually is pretty darn robust!

If you have other formats you want to be able to parse, please contribute tests! – And ideally a patch if the current code doesn’t work.

Converting to numbers:

Functions for returning tuples of numbers:

>>> to_dec_deg(23, 12, 3)
23.200833333333332
>>> to_deg_min(34.1234)
(34.0, 7.404)
>>> to_deg_min_sec(34.1234)
(34.0, 7, 24.24)

Converting to strings:

Functions for converting to various string formats:

>>> to_str_dec_deg(23, 12, 3)
'23.200833°'
>>> to_str_deg_min(2.345)
"2° 20.700'"
>>> to_str_deg_min_sec(-23.1234)
'-23° 7\' 24.24"'

>>> to_str(23.45)
'23.450000°'
>>> to_str(23, 45)
"23° 45.000'"
>>> to_str(23, 45, 6.7)
'23° 45\' 6.70"'

Usage with Pandas

Question from a user:

How to apply this lat_lon_parser on pandas dataframe specific column?

Turns out it’s straightforward – just pass the parse function to apply:

In [20]: df = pandas.DataFrame({'coords':["12d13'N","32 5 14", "30.123W"]})

In [21]: df
Out[21]:
    coords
0  12d13'N
1  32 5 14
2  30.123W

In [22]: df['coords'] = df['coords'].apply(parse)

In [23]: df
Out[23]:
      coords
0  12.216667
1  32.087222
2 -30.123000