"ValueError: The truth value of a Series is ambiguous" when passing pandas columns to a function

Question

I want to make a new column of type boolean based on the value of 4 other columns. I have a function is_proximal that takes two 2-tuples (the 4 values) and returns a boolean.

I am passing columns from a pandas DataFrame to this function. The is_proximal function in turn calls geopy.distance.distance with the arguments.

def is_proximal(p1, p2, exact=True):
    dist = distance(p1, p2)

    if exact:
        return dist.miles < 0.75  # mile threshold

    return dist.m < 100  # meter threshold



airbnb_coords = (df.loc[:, "lat_airbnb"], df.loc[:, "long_airbnb"])
homeaway_coords = (df.loc[:, "lat_homeaway"], df.loc[:, "long_homeaway"])
exacts.loc[:, "proximal"] = is_proximal(airbnb_coords, homeaway_coords)

This results in the following error:

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

I'm having trouble understanding why this error is occurring. What changes would I need to make to accomplish what I'm trying to do?

The expected output is an additional column of type boolean. The input dataframe df contains integer values in all columns.

The full traceback:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-663-435de26b3cfa> in <module>
----> 1 m = filter_geographic_proximity(beds)

~/src/exemption_project/src/match.py in filter_geographic_proximity(df)
     53     airbnb_coords = (exacts.loc[:, "lat_airbnb"], exacts.loc[:, "long_airbnb"])
     54     homeaway_coords = (exacts.loc[:, "lat_homeaway"], exacts.loc[:, "long_homeaway"])
---> 55     exacts.loc[:, "proximal"] = is_proximal(airbnb_coords, homeaway_coords)
     56 
     57     airbnb_coords = (inexacts.loc[:, "lat_airbnb"], inexacts.loc[:, "long_airbnb"])

~/src/exemption_project/src/match.py in is_proximal(p1, p2, exact)
     29 def filter_geographic_proximity(df):
     30     def is_proximal(p1, p2, exact=True):
---> 31         dist = distance(p1, p2)
     32 
     33         if exact:

~/.local/share/virtualenvs/exemption_project-xI6bzvA1/lib/python3.7/site-packages/geopy/distance.py in __init__(self, *args, **kwargs)
    387         kwargs.pop('iterations', 0)
    388         major, minor, f = self.ELLIPSOID
--> 389         super(geodesic, self).__init__(*args, **kwargs)
    390 
    391     def set_ellipsoid(self, ellipsoid):

~/.local/share/virtualenvs/exemption_project-xI6bzvA1/lib/python3.7/site-packages/geopy/distance.py in __init__(self, *args, **kwargs)
    162         elif len(args) > 1:
    163             for a, b in util.pairwise(args):
--> 164                 kilometers += self.measure(a, b)
    165 
    166         kilometers += units.kilometers(**kwargs)

~/.local/share/virtualenvs/exemption_project-xI6bzvA1/lib/python3.7/site-packages/geopy/distance.py in measure(self, a, b)
    408     # Call geographiclib routines for measure and destination
    409     def measure(self, a, b):
--> 410         a, b = Point(a), Point(b)
    411         lat1, lon1 = a.latitude, a.longitude
    412         lat2, lon2 = b.latitude, b.longitude

~/.local/share/virtualenvs/exemption_project-xI6bzvA1/lib/python3.7/site-packages/geopy/point.py in __new__(cls, latitude, longitude, altitude)
    163                     )
    164                 else:
--> 165                     return cls.from_sequence(seq)
    166 
    167         if single_arg:

~/.local/share/virtualenvs/exemption_project-xI6bzvA1/lib/python3.7/site-packages/geopy/point.py in from_sequence(cls, seq)
    403             raise ValueError('When creating a Point from sequence, it '
    404                              'must not have more than 3 items.')
--> 405         return cls(*args)
    406 
    407     @classmethod

~/.local/share/virtualenvs/exemption_project-xI6bzvA1/lib/python3.7/site-packages/geopy/point.py in __new__(cls, latitude, longitude, altitude)
    176 
    177         latitude, longitude, altitude = \
--> 178             _normalize_coordinates(latitude, longitude, altitude)
    179 
    180         self = super(Point, cls).__new__(cls)

~/.local/share/virtualenvs/exemption_project-xI6bzvA1/lib/python3.7/site-packages/geopy/point.py in _normalize_coordinates(latitude, longitude, altitude)
     57 
     58 def _normalize_coordinates(latitude, longitude, altitude):
---> 59     latitude = float(latitude or 0.0)
     60     longitude = float(longitude or 0.0)
     61     altitude = float(altitude or 0.0)

~/.local/share/virtualenvs/exemption_project-xI6bzvA1/lib/python3.7/site-packages/pandas/core/generic.py in __nonzero__(self)
   1476         raise ValueError("The truth value of a {0} is ambiguous. "
   1477                          "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
-> 1478                          .format(self.__class__.__name__))
   1479 
   1480     __bool__ = __nonzero__

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

Answer 1

From the traceback, it is clear that the error is being raised in the distance function that is_proximal is calling internally. This leads me to believe you're passing Series objects when the function is meant to be working with scalar data.

See the discussion in Truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all() where the use of python logical operators on pandas Series causes the same error.

In your case, the solution is to iterate over your data, and pass each group of co-ordinates to your function one at a time.

df['proximal'] = [
    is_proximal((a, b), (c, d)) 
    for a, b, c, d in df[['lat_x', 'long_x', 'lat_y', 'long_y']].values
]