lets_plot.scale_x_datetime

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

Position scale x for date/time data.

Parameters

namestr

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.

breakslist

A vector specifying values to display as ticks on axis.

labelslist of str

A vector of labels (on ticks).

limitslist

A vector of length two providing limits of the scale.

expandlist

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.

formatstr

Define 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.

positionstr

The position of the axis:

• ‘left’, ‘right’ or ‘both’ for y-axis;

• ‘top’, ‘bottom’ or ‘both’ for x-axis.

Returns

FeatureSpec

Scale specification.

Examples

import datetime as dt
import numpy as np
from lets_plot import *
LetsPlot.setup_html()
n = 31
np.random.seed(42)
d = [dt.datetime(2021, 1, 1) + dt.timedelta(days=d)
     for d in range(n)]
t = np.random.normal(loc=-5, scale=6, size=n)
ggplot({'d': d, 't': t}, aes('d', 't')) + \
    geom_histogram(aes(fill='t'), stat='identity', color='black') + \
    scale_x_datetime() + \
    scale_fill_gradient2(low='#2c7bb6', high='#d7191c')