verticapy.vDataFrame.plot#

Draws the time series.

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. If empty, all numerical vDataColumns are used.

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.

kind: str, optional

The plot type.

line:
Line Plot.
spline:
Spline Plot.
step:
Step Plot.
area_stacked:
Stacked Area Plot.
area_percent:
Fully Stacked Area Plot.

chart: PlottingObject, optional

The chart object to plot on.

**style_kwargs

Any optional parameter to pass to the plotting functions.

Returns#

obj: Plotting Object.

Examples#

Note

The below example is a very basic one. For other more detailed examples and customization options, please see Line Plots

Let’s begin by importing VerticaPy.

import verticapy as vp

Let’s also import numpy to create a dataset.

import numpy as np

Let’s generate a dataset using the following data.

data = vp.vDataFrame(
    {
        "date": [1900, 1950, 2000],
        "Asia": [947, 1402, 3634],
        "Africa": [133, 221, 767],
        "Europe": [408, 547, 729],
        "America": [156, 339, 818],
        "Oceania": [6, 13, 30],
    }
)

Below are examples of two types of plot plots:

Single
Multi

Single

data.plot(columns = ["Asia"], ts = "date", kind = "spline")

Multi

data.plot(columns = ["Asia", "Africa", "Europe", "America", "Oceania"], ts = "date")