Plots

This notebook presents some example of possible plots you can make using the package.

First, import the package

import dvb.datascience as ds

C:\ProgramData\Anaconda3\lib\site-packages\deap\tools\_hypervolume\pyhv.py:33: ImportWarning: Falling back to the python version of hypervolume module. Expect this to be very slow.
  "module. Expect this to be very slow.", ImportWarning)
C:\ProgramData\Anaconda3\lib\importlib\_bootstrap_external.py:426: ImportWarning: Not importing directory C:\ProgramData\Anaconda3\lib\site-packages\mpl_toolkits: missing __init__
  _warnings.warn(msg.format(portions[0]), ImportWarning)
C:\ProgramData\Anaconda3\lib\importlib\_bootstrap_external.py:426: ImportWarning: Not importing directory c:\programdata\anaconda3\lib\site-packages\mpl_toolkits: missing __init__
  _warnings.warn(msg.format(portions[0]), ImportWarning)

Boxplots

p = ds.Pipeline()
p.addPipe('read', ds.data.SampleData('iris'))
p.addPipe('boxplot', ds.eda.BoxPlot(), [("read", "df", "df")])
p.transform(name="boxplot_example", close_plt=True)

'Drawing diagram using blockdiag'

Transform boxplot_example

Boxplots Transform boxplot_example

ECDF plots

p = ds.Pipeline()
p.addPipe('read', ds.data.SampleData('iris'))
p.addPipe('ecdf', ds.eda.ECDFPlots(), [("read", "df", "df")])
p.transform(name="ecdf_example", close_plt=True)

'Drawing diagram using blockdiag'

Transform ecdf_example

ECDF Plots Transform ecdf_example

Scatter plots

p = ds.Pipeline()
p.addPipe('read', ds.data.SampleData('iris'))
p.addPipe('scatter', ds.eda.ScatterPlots(), [("read", "df", "df")])
p.transform(name="scatter_example", close_plt=True)

'Drawing diagram using blockdiag'

Transform scatter_example

Scatterplots Transform scatter_example

Histogram plots

p = ds.Pipeline()
p.addPipe('read', ds.data.SampleData('iris'))
p.addPipe('hist', ds.eda.Hist(), [("read", "df", "df")])
p.transform(name="histogram_example", close_plt=True)

'Drawing diagram using blockdiag'

Transform histogram_example

Histogram Transform histogram_example

Swarm plots

p = ds.Pipeline()
p.addPipe('read', ds.data.SampleData('iris'))
p.addPipe('swarm', ds.eda.SwarmPlots(), [("read", "df", "df")])
p.transform(name="swarm_example")

'Drawing diagram using blockdiag'

Transform swarm_example

Swarmplots Transform swarm_example

Dimensionality reduction plots

p = ds.Pipeline()
p.addPipe('read', ds.data.SampleData('iris'))
p.addPipe('dimred', ds.eda.DimensionReductionPlots("target"), [("read", "df", "df")])
p.fit_transform(name="dimensionality_reduction_example", close_plt=True)

'Drawing diagram using blockdiag'

Transform dimensionality_reduction_example

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\manifold\spectral_embedding_.py:234: UserWarning: Graph is not fully connected, spectral embedding may not work as expected.
  warnings.warn("Graph is not fully connected, spectral embedding"

C:\ProgramData\Anaconda3\lib\site-packages\sklearn\neighbors\base.py:371: RuntimeWarning: invalid value encountered in sqrt
  result = np.sqrt(dist[sample_range, neigh_ind]), neigh_ind

Andrews curves plots

p = ds.Pipeline()
p.addPipe('read', ds.data.SampleData('iris'))
p.addPipe('andrews', ds.eda.AndrewsPlot(column="target"), [("read", "df", "df")])
p.transform(name="andrews", close_plt=True)

'Drawing diagram using blockdiag'

Transform andrews

Andrews curves Transform andrews