I’m trying to find distances between all points (latitude, longitude), and for each point, get the average price_area (price/area) of the closest points around it. This code is taking too long:
def create_pa_radius(df, radius): df['pa_' + str(radius)] = np.nan for index, row in df.iterrows(): point = [row['latitude'], row['longitude']] df['distances'] = df.apply(lambda x: geo_dist(point, [x['latitude'], x['longitude']]).km, axis = 1) samples = df.price_area[df.distances < radius/1000] mean = samples.mean() df['pa_' + str(radius)].iloc[index] = mean return df
I would like at least to understand how to make this kind of iteration faster.
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