Compositing Correlation Plot | teradataml - Compositing Correlation Plot - Teradata Package for Python

Teradata® Package for Python User Guide

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Teradata Package for Python
Release Number
20.00
Published
March 2024
Language
English (United States)
Last Update
2024-04-09
dita:mapPath
nvi1706202040305.ditamap
dita:ditavalPath
plt1683835213376.ditaval
dita:id
rkb1531260709148
Product Category
Teradata Vantage

Example

  • >>> load_example_data("uaf", ["acf"])
    
  • >>> df = DataFrame("acf")
    >>> df
        ROW_I     OUT_v  CONF_OFF_v  CONF_LOW_v  CONF_HI_v
    id
    1       2  0.828499    0.484255    0.344244   1.312753
    1       4  0.481562    0.653203   -0.171641   1.134765
    1       5  0.274737    0.682560   -0.407822   0.957297
    1       6  0.064830    0.691846   -0.627016   0.756677
    1       8 -0.310745    0.694562   -1.005307   0.383817
    1       9 -0.454362    0.706218   -1.160581   0.251856
    1       7 -0.134393    0.692360   -0.826753   0.557967
    1       3  0.670858    0.592091    0.078767   1.262949
    1       1  0.941700    0.290772    0.650928   1.232471
    1       0  1.000000    0.000000    1.000000   1.000000
    >>>
    
  • >>> ndf = df.assign(OUT_v2=df.OUT_v * 2, CONF_OFF_v2=df.CONF_OFF_v * 2)
    >>> ndf.plot(x=ndf.ROW_I, y=[(ndf.OUT_v, ndf.CONF_OFF_v), (ndf.OUT_v2, ndf.CONF_OFF_v2)],
    ...          kind='corr', color=["orange", "brown"], legend=["out1", "out2"])

    composite correlation plot