gist

#CrossCompute

outcome_select = """
    Graduation Rate

    Graduation Rate
    Dropped Out - % of cohort
    Total Regents - % of cohort
"""
attribute_select = """
    Diversity Index

    Diversity Index
    economic_need_index
    students_with_disabilities_1
"""
target_folder = '/tmp'

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

# Fixing random state for reproducibility
np.random.seed(19680801)

#N = 50
#x = np.random.rand(N)
#y = np.random.rand(N)
colors = np.random.rand(N)
area = (30 * np.random.rand(N))**2  # 0 to 15 point radii

axes = plt.scatter(x, y, s=area, c=colors, alpha=0.5)
plt.show()

# Save file to target folder to include it in the result download
target_path = target_folder + '/c.png'
figure = axes.get_figure()
figure.savefig(target_path)
print(f'c_image_path = {target_path}')

url = 'https://data.cityofnewyork.us/api/geospatial/r8nu-ymqj?method=export&format=Shapefile'

import geotable

dist_table = geotable.load(url)

dist_table.iloc[0]