CODEWITHSUNDEEP
pythonpandasgeolocationgeopy
spidermarn
spidermarn

Reputation: 939

Python how to create a new column that measures proximity to a city?

I have a dataframe with Latitude and Longitude columns,

df = pd.DataFrame({'Latitude':[47.5112, 47.7210, 47.7379, 47.5208, 47.6168],
                    'Longitude':[-122.257, -122.319, -122.233, -122.393, -122.045]})

How do I create a column that measures the distance towards a particular location with coordinates (47.631872, -122.217109)

In particular I'd like to use the geodesic function from geopy for the distance: from geopy.distance import geodesic. It takes in the inputs of 2 tuples containing latitudes and longitudes, and outputs the distance.

Upvotes: 1

Views: 744

Answers (2)

Dishin H Goyani
Dishin H Goyani

Reputation: 7693

Use apply

location = (47.631872, -122.217109)
df["distance"] = df.apply(lambda x:geodesic((x["Latitude"], x["Longitude"]), location), axis=1)

Upvotes: 2

Code Ninja 2C4U
Code Ninja 2C4U

Reputation: 114

Assuming you want to create a new column within the DataFrame with the desired distance:

location = (40.5, 47.7) # example of coordinates of your desired location, change as needed

df["Distance To Location"] = geodesic((df["Latitude"],df["Longitude"]),location)

Your dataframe will now have a 3rd column with a pointer to a pandas Series of geodesic objects from each lat/long row and location coordinates provided.

Optionally if you only want the actual distance value (float) in say "miles" you can do something like this:

# To get the float value of the distance in miles
df["Distance To Location"] = geodesic((df["Latitude"],df["Longitude"]),location).miles

And it should save the float value in miles for each row directly into your dataframe.

Upvotes: 1

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