lets_plot.scale_y_datetime

lets_plot.scale_y_datetime(name=None, breaks=None, labels=None, limits=None, expand=None, na_value=None, format=None)

Position scale y for date/time data.

Parameters
  • name (str) – The name of the scale - used as the axis label or the legend title. If None, the default, the name of the scale is taken from the first mapping used for that aesthetic.

  • breaks (list) – A numeric vector of positions (of ticks).

  • labels (list of str) – A vector of labels (on ticks).

  • limits (list) – A numeric vector of length two providing limits of the scale.

  • expand (list of two numbers) – A numeric vector of length two giving multiplicative and additive expansion constants. The vector size == 1 => only multiplicative expand (and additive expand by default). Defaults: multiplicative = 0.05, additive = 0.

  • na_value – Missing values will be replaced with this value.

  • format (str) – Defines the format for labels on the scale. The syntax resembles Python’s: ‘%d.%m.%y’ -> ‘06.08.19’ ‘%B %Y’ -> ‘August 2019’ ‘%a, %e %b %Y %H:%M:%S’ -> ‘Tue, 6 Aug 2019 04:46:35’ For more info see https://lets-plot.org/pages/formats.html.

Returns

Scale specification.

Return type

FeatureSpec

Examples

 1import datetime as dt
 2from lets_plot import *
 3LetsPlot.setup_html()
 4n = 12
 5rcount = lambda m: 1 if m < 2 else rcount(m - 1) + rcount(m - 2)
 6data = {
 7    'date': [dt.datetime(2020, m, 1) for m in range(1, n + 1)],
 8    'rabbits count': [rcount(m) for m in range(1, n + 1)],
 9}
10ggplot(data) + \
11    geom_segment(aes(x=[0] * n, y='date', xend='rabbits count', yend='date'), size=3, \
12                 tooltips=layer_tooltips().line('@|@{rabbits count}')) + \
13    scale_y_datetime(format='%b') + \
14    xlab('rabbits count')