l = df['pickup_longitude']
return df[(l < -70) & (l > -80)]
def print_len(x):
if x is not None:
print(len(x))
#log_level()
try:
s = scheduler
except:
s = Scheduler()
csv = CSVLoader(get_dataset('bigfile'),
header=None,
index_col=False,
force_valid_ids=True,
scheduler=s)
pr = Every(scheduler=s)
pr.input.df = csv.output.table
scatterplot = ScatterPlot(x_column='_1', y_column='_2', scheduler=s)
scatterplot.create_dependent_modules(csv, 'table')
if __name__ == '__main__':
csv.start()
s.join()
print(len(csv.df()))
"""
Clustering datasets may be found at
https://cs.joensuu.fi/sipu/datasets/
"""
from progressivis import Scheduler, Every#, log_level
from progressivis.cluster import MBKMeans
from progressivis.io import CSVLoader
from progressivis.vis import ScatterPlot
from progressivis.datasets import get_dataset
try:
s = scheduler
except NameError:
s = Scheduler()
#log_level(package="progressivis.cluster")
data = CSVLoader(get_dataset('cluster:s1'),sep='\\s+',skipinitialspace=True,header=None,index_col=False,scheduler=s)
mbkmeans = MBKMeans(columns=['_0', '_1'], n_clusters=15, batch_size=100, is_input=False, scheduler=s)
mbkmeans.input.table = data.output.table
prn = Every(scheduler=s)
prn.input.df = mbkmeans.output.table
sp = ScatterPlot('_0','_1', scheduler=s)
sp.move_point = mbkmeans # for input management
sp.create_dependent_modules(data,'table', sample=None, select=mbkmeans)
if __name__ == '__main__':
data.start()
s.join()
from progressivis import Scheduler, Print
from progressivis.cluster import MBKMeans
from progressivis.stats import RandomTable
from progressivis.vis import ScatterPlot
try:
s = scheduler
except:
s = Scheduler()
table = RandomTable(columns=['a', 'b'], rows=50000, throttle=500, scheduler=s)
mbkmeans = MBKMeans(columns=['a', 'b'], n_clusters=8, batch_size=100, is_input=False, scheduler=s)
mbkmeans.input.table = table.output.table
prn = Print(scheduler=s)
prn.input.df = mbkmeans.output.table
sp = ScatterPlot('a', 'b', scheduler=s)
sp.create_dependent_modules(mbkmeans,'table')
if __name__ == '__main__':
table.start()
