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

Position scale x for date/time data.

  • 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) – 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.


Scale specification.

Return type



 1import datetime as dt
 2import numpy as np
 3from lets_plot import *
 5n = 31
 7d = [dt.datetime(2021, 1, 1) + dt.timedelta(days=d)
 8     for d in range(n)]
 9t = np.random.normal(loc=-5, scale=6, size=n)
10ggplot({'d': d, 't': t}, aes('d', 't')) + \
11    geom_histogram(aes(fill='t'), stat='identity', color='black') + \
12    scale_x_datetime() + \
13    scale_fill_gradient2(low='#2c7bb6', high='#d7191c')