applying a lambda function to pandas dataframe - python-3.x

Question

First time posting on stackoverflow, so bear with me if I'm making some faux pas please :)
I'm trying to calculate the distance between two points, using geopy, but I can't quite get the actual application of the calculation to work.
Here's the head of the dataframe I'm working with (there are some missing values later in the dataframe, not sure if this is the issue or how to handle it in general):
start lat start long end_lat end_long
0 38.902760 -77.038630 38.880300 -76.986200
2 38.895914 -77.026064 38.915400 -77.044600
3 38.888251 -77.049426 38.895914 -77.026064
4 38.892300 -77.043600 38.888251 -77.049426
I've set up a function:
def dist_calc(st_lat, st_long, fin_lat, fin_long):
from geopy.distance import vincenty
start = (st_lat, st_long)
end = (fin_lat, fin_long)
return vincenty(start, end).miles
This one works fine when given manual input.
However, when I try to apply() the function, I run into trouble with the below code:
distances = df.apply(lambda row: dist_calc(row[-4], row[-3], row[-2], row[-1]), axis=1)
I'm fairly new to python, any help will be much appreciated!
Edit: error message:
distances = df.apply(lambda row: dist_calc2(row[-4], row[-3], row[-2], row[-1]), axis=1)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/pandas/core/frame.py", line 4262, in apply
ignore_failures=ignore_failures)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/pandas/core/frame.py", line 4358, in _apply_standard
results[i] = func(v)
File "<stdin>", line 1, in <lambda>
File "<stdin>", line 5, in dist_calc2
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/geopy/distance.py", line 322, in __init__
super(vincenty, self).__init__(*args, **kwargs)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/geopy/distance.py", line 115, in __init__
kilometers += self.measure(a, b)
File "/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/geopy/distance.py", line 414, in measure
u_sq = cos_sq_alpha * (major ** 2 - minor ** 2) / minor ** 2
UnboundLocalError: ("local variable 'cos_sq_alpha' referenced before assignment", 'occurred at index 10')

Answer 1

The default settings for pandas functions typically used to import text data like this (pd.read_table() etc) will interpret the spaces in the first 2 column names as separators, so you'll end up with 6 columns instead of 4, and your data will be misaligned:
In [23]: df = pd.read_clipboard()
In [24]: df
Out[24]:
start lat start.1 long end_lat end_long
0 0 38.902760 -77.038630 38.880300 -76.986200 NaN
1 2 38.895914 -77.026064 38.915400 -77.044600 NaN
2 3 38.888251 -77.049426 38.895914 -77.026064 NaN
3 4 38.892300 -77.043600 38.888251 -77.049426 NaN
In [25]: df.columns
Out[25]: Index(['start', 'lat', 'start.1', 'long', 'end_lat', 'end_long'], dtype='object')
Notice column names are wrong, the last column is full of NaNs, etc. If I apply your function to the dataframe in this form, I get the same error as you did.
Its usually better to try to fix this before it gets imported as a dataframe. I can think of 2 methods:
clean the data before importing, for example copy it into an editor and replace the offending spaces with underscores. This is the easiest.
use a regex to fix it during import. This may be necessary if the dataset is very large, or its is pulled from a website and has to be refreshed regularly.
Here's an example of case (2):
In [35]: df = pd.read_clipboard(sep=r'\s{2,}|\s(?=-)', engine='python')
In [36]: df = df.rename_axis({'start lat': 'start_lat', 'start long': 'start_long'}, axis=1)
In [37]: df
Out[37]:
start_lat start_long end_lat end_long
0 38.902760 -77.038630 38.880300 -76.986200
2 38.895914 -77.026064 38.915400 -77.044600
3 38.888251 -77.049426 38.895914 -77.026064
4 38.892300 -77.043600 38.888251 -77.049426
The specified that separators must contain either 2+ whitespaces characters, or 1 whitespace followed by a hyphen (minus sign). Then I rename the columns to what i assume are the expected values.
From this point your function / apply works fine, but i've changed it a little:
PEP8 recommends putting imports at the top of each file, rather than in a function
Extracting the columns by name is more robust, and would have given a much more understandable error than the weird error thrown by geopy.
For example:
In [51]: def dist_calc(row):
...: start = row[['start_lat','start_long']]
...: end = row[['end_lat', 'end_long']]
...: return vincenty(start, end).miles
...:
In [52]: df.apply(lambda row: dist_calc(row), axis=1)
Out[52]:
0 3.223232
2 1.674780
3 1.365851
4 0.420305
dtype: float64