Calculating the centroid
The bounding box can range from a city block to a whole state or even country. For simplicity's sake, one way we can deal with handling these data is by translating the bounding box into what's called a centroid, or the center of the bounding box. The calculation of the centroid is straight forward -- we calculate the midpoints of the lines created by the latitude and longitudes.
numpy has been imported as np.
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Analyzing Social Media Data in Python
Hướng dẫn bài tập
- Obtain the first set of coordinates from the place JSON.
- Calculate the central longitude by adding up the longitude list and dividing by two.
- Do the same for the latitudes.
- Apply the
calculateCentroid()function to theplacecolumn.
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def calculateCentroid(place):
""" Calculates the centroid from a bounding box."""
# Obtain the coordinates from the bounding box.
coordinates = place[____][____][0]
longs = np.unique( [x[0] for x in coordinates] )
lats = np.unique( [x[1] for x in coordinates] )
if len(longs) == 1 and len(lats) == 1:
# return a single coordinate
return (longs[0], lats[0])
elif len(longs) == 2 and len(lats) == 2:
# If we have two longs and lats, we have a box.
central_long = ____.____(____) / ____
central_lat = ____.____(____) / ____
else:
raise ValueError("Non-rectangular polygon not supported: %s" %
",".join(map(lambda x: str(x), coordinates)) )
return (central_long, central_lat)
# Calculate the centroids of place
centroids = tweets_sotu[____].apply(____)