vDataFrame.density¶

In [ ]:

vDataFrame.density(columns: list = [],
                   bandwidth: float = 1.0,
                   kernel: str = "gaussian",
                   nbins: int = 200,
                   xlim = None,
                   ax=None,
                   **style_kwds,)

Draws the vcolumns Density Plot.

Parameters¶

Name	Type	Optional	Description
columns	list	✓	List of the vcolumns names. If empty, all the numerical vcolumns will be selected.
bandwidth	float	✓	The bandwidth of the kernel.
kernel	str	✓	The method used for the plot. gaussian : Gaussian Kernel. logistic : Logistic Kernel. sigmoid : Sigmoid Kernel. silverman : Silverman Kernel.
nbins	int	✓	Maximum number of points to use to evaluate the approximate density function. Increasing this parameter will increase the precision but will also increase the time of the learning and scoring phases.
xlim	tuple	✓	Set the x limits of the current axes.
ax	Matplotlib axes object	✓	The axes to plot on.
**style_kwds	any	✓	Any optional parameter to pass to the Matplotlib functions.

Returns¶

ax : Matplotlib axes object

Example¶

In [1]:

from verticapy.datasets import load_iris
iris = load_iris()
display(iris)

	123 SepalLengthCm Numeric(5,2)	123 SepalWidthCm Numeric(5,2)	123 PetalLengthCm Numeric(5,2)	123 PetalWidthCm Numeric(5,2)	Abc Species Varchar(30)
1	4.3	3.0	1.1	0.1	Iris-setosa
2	4.4	2.9	1.4	0.2	Iris-setosa
3	4.4	3.0	1.3	0.2	Iris-setosa
4	4.4	3.2	1.3	0.2	Iris-setosa
5	4.5	2.3	1.3	0.3	Iris-setosa
6	4.6	3.1	1.5	0.2	Iris-setosa
7	4.6	3.2	1.4	0.2	Iris-setosa
8	4.6	3.4	1.4	0.3	Iris-setosa
9	4.6	3.6	1.0	0.2	Iris-setosa
10	4.7	3.2	1.3	0.2	Iris-setosa
11	4.7	3.2	1.6	0.2	Iris-setosa
12	4.8	3.0	1.4	0.1	Iris-setosa
13	4.8	3.0	1.4	0.3	Iris-setosa
14	4.8	3.1	1.6	0.2	Iris-setosa
15	4.8	3.4	1.6	0.2	Iris-setosa
16	4.8	3.4	1.9	0.2	Iris-setosa
17	4.9	2.4	3.3	1.0	Iris-versicolor
18	4.9	2.5	4.5	1.7	Iris-virginica
19	4.9	3.0	1.4	0.2	Iris-setosa
20	4.9	3.1	1.5	0.1	Iris-setosa
21	4.9	3.1	1.5	0.1	Iris-setosa
22	4.9	3.1	1.5	0.1	Iris-setosa
23	5.0	2.0	3.5	1.0	Iris-versicolor
24	5.0	2.3	3.3	1.0	Iris-versicolor
25	5.0	3.0	1.6	0.2	Iris-setosa
26	5.0	3.2	1.2	0.2	Iris-setosa
27	5.0	3.3	1.4	0.2	Iris-setosa
28	5.0	3.4	1.5	0.2	Iris-setosa
29	5.0	3.4	1.6	0.4	Iris-setosa
30	5.0	3.5	1.3	0.3	Iris-setosa
31	5.0	3.5	1.6	0.6	Iris-setosa
32	5.0	3.6	1.4	0.2	Iris-setosa
33	5.1	2.5	3.0	1.1	Iris-versicolor
34	5.1	3.3	1.7	0.5	Iris-setosa
35	5.1	3.4	1.5	0.2	Iris-setosa
36	5.1	3.5	1.4	0.2	Iris-setosa
37	5.1	3.5	1.4	0.3	Iris-setosa
38	5.1	3.7	1.5	0.4	Iris-setosa
39	5.1	3.8	1.5	0.3	Iris-setosa
40	5.1	3.8	1.6	0.2	Iris-setosa
41	5.1	3.8	1.9	0.4	Iris-setosa
42	5.2	2.7	3.9	1.4	Iris-versicolor
43	5.2	3.4	1.4	0.2	Iris-setosa
44	5.2	3.5	1.5	0.2	Iris-setosa
45	5.2	4.1	1.5	0.1	Iris-setosa
46	5.3	3.7	1.5	0.2	Iris-setosa
47	5.4	3.0	4.5	1.5	Iris-versicolor
48	5.4	3.4	1.5	0.4	Iris-setosa
49	5.4	3.4	1.7	0.2	Iris-setosa
50	5.4	3.7	1.5	0.2	Iris-setosa
51	5.4	3.9	1.3	0.4	Iris-setosa
52	5.4	3.9	1.7	0.4	Iris-setosa
53	5.5	2.3	4.0	1.3	Iris-versicolor
54	5.5	2.4	3.7	1.0	Iris-versicolor
55	5.5	2.4	3.8	1.1	Iris-versicolor
56	5.5	2.5	4.0	1.3	Iris-versicolor
57	5.5	2.6	4.4	1.2	Iris-versicolor
58	5.5	3.5	1.3	0.2	Iris-setosa
59	5.5	4.2	1.4	0.2	Iris-setosa
60	5.6	2.5	3.9	1.1	Iris-versicolor
61	5.6	2.7	4.2	1.3	Iris-versicolor
62	5.6	2.8	4.9	2.0	Iris-virginica
63	5.6	2.9	3.6	1.3	Iris-versicolor
64	5.6	3.0	4.1	1.3	Iris-versicolor
65	5.6	3.0	4.5	1.5	Iris-versicolor
66	5.7	2.5	5.0	2.0	Iris-virginica
67	5.7	2.6	3.5	1.0	Iris-versicolor
68	5.7	2.8	4.1	1.3	Iris-versicolor
69	5.7	2.8	4.5	1.3	Iris-versicolor
70	5.7	2.9	4.2	1.3	Iris-versicolor
71	5.7	3.0	4.2	1.2	Iris-versicolor
72	5.7	3.8	1.7	0.3	Iris-setosa
73	5.7	4.4	1.5	0.4	Iris-setosa
74	5.8	2.6	4.0	1.2	Iris-versicolor
75	5.8	2.7	3.9	1.2	Iris-versicolor
76	5.8	2.7	4.1	1.0	Iris-versicolor
77	5.8	2.7	5.1	1.9	Iris-virginica
78	5.8	2.7	5.1	1.9	Iris-virginica
79	5.8	2.8	5.1	2.4	Iris-virginica
80	5.8	4.0	1.2	0.2	Iris-setosa
81	5.9	3.0	4.2	1.5	Iris-versicolor
82	5.9	3.0	5.1	1.8	Iris-virginica
83	5.9	3.2	4.8	1.8	Iris-versicolor
84	6.0	2.2	4.0	1.0	Iris-versicolor
85	6.0	2.2	5.0	1.5	Iris-virginica
86	6.0	2.7	5.1	1.6	Iris-versicolor
87	6.0	2.9	4.5	1.5	Iris-versicolor
88	6.0	3.0	4.8	1.8	Iris-virginica
89	6.0	3.4	4.5	1.6	Iris-versicolor
90	6.1	2.6	5.6	1.4	Iris-virginica
91	6.1	2.8	4.0	1.3	Iris-versicolor
92	6.1	2.8	4.7	1.2	Iris-versicolor
93	6.1	2.9	4.7	1.4	Iris-versicolor
94	6.1	3.0	4.6	1.4	Iris-versicolor
95	6.1	3.0	4.9	1.8	Iris-virginica
96	6.2	2.2	4.5	1.5	Iris-versicolor
97	6.2	2.8	4.8	1.8	Iris-virginica
98	6.2	2.9	4.3	1.3	Iris-versicolor
99	6.2	3.4	5.4	2.3	Iris-virginica
100	6.3	2.3	4.4	1.3	Iris-versicolor

Rows: 1-100 | Columns: 5

In [4]:

iris.density()

Out[4]:

<AxesSubplot:title={'center':'KernelDensity'}, ylabel='density'>

In [5]:

# Density using 10 points
iris.density(nbins=10)

Out[5]:

<AxesSubplot:title={'center':'KernelDensity'}, ylabel='density'>

In [6]:

# Logistic Kernel
iris.density(kernel = "logistic")

Out[6]:

<AxesSubplot:title={'center':'KernelDensity'}, ylabel='density'>

In [7]:

# Using xlim
iris.density(xlim = [0, 10])

Out[7]:

<AxesSubplot:title={'center':'KernelDensity'}, ylabel='density'>

vDataFrame.density¶

Parameters¶

Returns¶

Example¶

See Also¶