[' -80.82581786107986,39.83903198141125,0 -80.82377033116026,39.83364133601582,0 -80.82356083750963,39.82911201506083,0 -80.82285757569279,39.82686138006091,0']
I extracted coordinates from a KML file with 3 polygons and one of the polygon's coordinates are stored in the one element of the list. I want to calculate the min of the longitude and latitude respectively. Does anyone know how to do that?
Do I need to split the list somehow and then proceed?
Very much appreciated!
I think this is what you are looking for. Note: In Python 2.x
I take the single string, strip the outer whitespace, the split the values on whitespace or commas. That yields this array, which you can loop over in groups to get values.
['-80.82581786107986', '39.83903198141125', '0', '-80.82377033116026', '39.83364133601582', '0', '-80.82356083750963', '39.82911201506083', '0', '-80.82285757569279', '39.82686138006091', '0']
import re
l = [' -80.82581786107986,39.83903198141125,0 -80.82377033116026,39.83364133601582,0 -80.82356083750963,39.82911201506083,0',
'-80.82285757569279,39.82686138006091,0 -80.82211394716366,39.82370641582035,0 -80.82079041778377,39.82101855094219,0',
' -80.82008287730855,39.84462640578131,0 -80.82581786107986,39.83903198141125,0']
for s in l:
parts = map(float, re.split(r'[,\s+]', s.strip()))
lats = []
longs = []
for i in range(0, len(parts), 3):
long = parts[i]
lat = parts[i+1]
longs.append(long)
lats.append(lat)
print min(lats), min(longs)
Output
39.8291120151 -80.8258178611
39.8210185509 -80.8228575757
39.8390319814 -80.8258178611
float, no?Using list comprehension, str.split() and str.strip methods:
l = [' -80.82581786107986,39.83903198141125,0 -80.82377033116026,39.83364133601582,0 -80.82356083750963,39.82911201506083,0 -80.82285757569279,39.82686138006091,0']
res = [list(map(float, coord.split(','))) for coord in l[0].strip().split()]
In [217]: res
Out[217]:
[[-80.82581786107986, 39.83903198141125, 0.0],
[-80.82377033116026, 39.83364133601582, 0.0],
[-80.82356083750963, 39.82911201506083, 0.0],
[-80.8228575756928, 39.82686138006091, 0.0]]
To calculate the min and longtitude and latitude you could convert that list to np.array for easy manipulation and use ndarray method min with axis=0 or np.amin:
import numpy as np
arr = np.array(res)
In [221]: arr
Out[221]:
array([[-80.82581786, 39.83903198, 0. ],
[-80.82377033, 39.83364134, 0. ],
[-80.82356084, 39.82911202, 0. ],
[-80.82285758, 39.82686138, 0. ]])
In [224]: arr.min(axis=0)
Out[224]: array([-80.82581786, 39.82686138, 0. ])
In [226]: np.amin(arr, axis=0)
Out[226]: array([-80.82581786, 39.82686138, 0. ])
map with float which means convert str to float.here you go:
>>> my_list = [' -80.82581786107986,39.83903198141125,0 -80.82377033116026,39.83364133601582,0 -80.82356083750963,39.82911201506083,0 -80.82285757569279,39.82686138006091,0']
>>> map(lambda x: map(float, x.split(",")), my_list[0].strip().split())
[[-80.82581786107986, 39.83903198141125, 0.0], [-80.82377033116026, 39.83364133601582, 0.0], [-80.82356083750963, 39.82911201506083, 0.0], [-80.8228575756928, 39.82686138006091, 0.0]]
Mean of latitude and longitude:
>>> map(lambda x: (x[0]+x[1])/2, map(lambda x: map(float, x.split(",")), my_list[0].strip().split()))
[-20.4933929398343, -20.49506449757222, -20.4972244112244, -20.49799809781594]
you can use pandas too:
>>> import `pandas` as pd
>>> pd.DataFrame(map(lambda x: map(float, x.split(",")), my_list[0].strip().split()))
0 1 2
0 -80.825818 39.839032 0
1 -80.823770 39.833641 0
2 -80.823561 39.829112 0
3 -80.822858 39.826861 0
>>> data = pd.DataFrame(map(lambda x: map(float, x.split(",")), my_list[0].strip().split()))
>>> data.mean()
0 -80.824002
1 39.832162
2 0.000000
dtype: float64
