module timeseries.plotting#

Short summary#

module mlinsights.timeseries.plotting

Timeseries plots.

source on GitHub

Functions#

function

truncated documentation

plot_week_timeseries

Shows a timeseries dispatched by days as bars.

Documentation#

Timeseries plots.

source on GitHub

mlinsights.timeseries.plotting.plot_week_timeseries(time, value, normalise=True, label=None, h=0.85, value2=None, label2=None, daynames=None, xfmt='%1.0f', ax=None)#

Shows a timeseries dispatched by days as bars.

Parameters
  • time – dates

  • value – values to display as bars.

  • normalise – normalise data before showing it

  • label – label of the series

  • values2 – second series to show as a line

  • label2 – label of the second series

  • daynames – names to use for week day names (default is English)

  • xfmt – format number of the X axis

  • ax – existing axis

Returns

axis

import datetime
import matplotlib.pyplot as plt
from mlinsights.timeseries.datasets import artificial_data
from mlinsights.timeseries.agg import aggregate_timeseries
from mlinsights.timeseries.plotting import plot_week_timeseries

dt1 = datetime.datetime(2019, 8, 1)
dt2 = datetime.datetime(2019, 9, 1)
data = artificial_data(dt1, dt2, minutes=15)
print(data.head())

agg = aggregate_timeseries(data, per='week')
plot_week_timeseries(
    agg['weektime'], agg['y'], label="y",
    value2=agg['y']/2, label2="y/2", normalise=False)
plt.show()

(png, hires.png, pdf)

../../_images/plotting-1.png

source on GitHub