verticapy.vDataFrame.animated_plot#

Draws the animated line plot.

Parameters#

ts: str: TS (Time Series) vDataColumn used to order the data. The vDataColumn type must be date (date, datetime, timestamp…) or numerical.
columns: SQLColumns, optional: List of the vDataColumns names.
by: str, optional: Categorical vDataColumn used in the partition.
start_date: PythonScalar, optional: Input Start Date. For example, time = ‘03-11-1993’ will filter the data when ‘ts’ is less than the 3rd of November 1993.
end_date: PythonScalar, optional: Input End Date. For example, time = ‘03-11-1993’ will filter the data when ‘ts’ is greater than the 3rd of November 1993.
limit_over: int, optional: Limited number of elements to consider for each category.
limit: int, optional: Maximum number of data points to use.
step: int, optional: Number of elements used to update the time series.
window_size: int, optional: Size of the window used to draw the time series.
fixed_xy_lim: bool, optional: If set to True, the xlim and ylim are fixed.
interval: int, optional: Number of ms between each update.
repeat: bool, optional: If set to True, the animation is repeated.
chart: PlottingObject, optional: The chart object used to plot.
**style_kwargs: Any optional parameter to pass to the plotting functions.

Note

The below example is a very basic one. For other more detailed examples and customization options, please see :ref:`chart_gallery.animated`_

Let’s begin by importing VerticaPy.

import verticapy as vp

import verticapy.datasets as vpd

Let’s import the dataset:

commodities = vpd.load_commodities()

Now we can finally create the plot:

commodities.animated_plot(ts = "date")