Repository for Petra's work at ampli Jan-Feb 2019

clustering.py 492B

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  1. from util import getQuery
  2. import pandas as p
  3. import matplotlib.pyplot as plt
  4. import seaborn as sns
  5. query = """
  6. SELECT icp_id, read_date + CONCAT(period / 2, ':', period %% 2 * 30, ':00')::time AS read_time,
  7. kwh_tot
  8. FROM public.coup_tall_april WHERE icp_id LIKE (%s) ORDER BY icp_id, read_time;
  9. """
  10. qparams = ['%%1117']
  11. df = getQuery(query, qparams)
  12. print(df.info())
  13. sns.set()
  14. sns.scatterplot(x = 'read_time', y = 'kwh_tot', hue = 'icp_id', style = 'icp_id', data = df)
  15. plt.show()