verticapy.vDataFrame.hist#
- vDataFrame.hist(columns: str | list[str], method: Literal['density', 'count', 'avg', 'min', 'max', 'sum'] | str = 'density', of: str | None = None, h: int | float | Decimal | None = None, chart: PlottingBase | TableSample | Axes | mFigure | Highchart | Highstock | Figure | None = None, **style_kwargs) PlottingBase | TableSample | Axes | mFigure | Highchart | Highstock | Figure #
Draws the histograms of the input vDataColumns based on an aggregation.
Parameters#
- columns: SQLColumns
list
of thevDataColumns
names. Thelist
must have less than 5 elements.- method: str, optional
The method used to aggregate the data.
- count:
Number of elements.
- density:
Percentage of the distribution.
- mean:
Average of the
vDataColumns
of
.
- min:
Minimum of the
vDataColumns
of
.
- max:
Maximum of the
vDataColumns
of
.
- sum:
Sum of the
vDataColumns
of
.
- q%:
q Quantile of the
vDataColumns
of
(ex: 50% to get the median).
It can also be a cutomized aggregation, for example:
AVG(column1) + 5
- of: str, optional
The
vDataColumns
used to compute the aggregation.- h: tuple, optional
Interval width of the input vDataColumns. Optimized h will be computed if the parameter is empty or invalid.
- 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 Histogram
Let’s begin by importing VerticaPy.
import verticapy as vp
Let’s also import numpy to create a dataset.
import numpy as np
We can create a variable
N
to fix the size:N = 50
Let’s generate a dataset using the following data.
data = vp.vDataFrame( { "score1": np.random.normal(5, 1, N), "score2": np.random.normal(8, 1.5, N), "score3": np.random.normal(10, 2, N), } )
Below are examples of two types of hist plots:
Single
Multi
data.hist(["score1"])
data.hist(columns = ["score1", "score2"])