Interactive or non-interactive visualization in Jupyter (Python version)?

from beakerx import *
from beakerx.object import beakerx
beakerx.pandas_display_default()

from matplotlib import pyplot as plt
%matplotlib inline

sns.pairplot(df, hue="species")

import plotly.express as px
# df = px.data.iris()
fig = px.scatter_matrix(df,
    dimensions=["sepal_width", "sepal_length", "petal_width", "petal_length"],
    color="species", symbol="species",
    title="Scatter matrix of iris data set",
    labels={col:col.replace('_', ' ') for col in df.columns})
fig.update_traces(diagonal_visible=False)
fig.show()

%matplotlib inline
import matplotlib.pyplot as plt # side-stepping mpl backend
import matplotlib.gridspec as gridspec # subplots
import numpy as np

fig1 = plt.figure()
# Make a legend for specific lines.
import matplotlib.pyplot as plt
import numpy as np


t1 = np.arange(0.0, 2.0, 0.1)
t2 = np.arange(0.0, 2.0, 0.01)

# note that plot returns a list of lines.  The "l1, = plot" usage
# extracts the first element of the list into l1 using tuple
# unpacking.  So l1 is a Line2D instance, not a sequence of lines
l1, = plt.plot(t2, np.exp(-t2))
l2, l3 = plt.plot(t2, np.sin(2 * np.pi * t2), '--go', t1, np.log(1 + t1), '.')
l4, = plt.plot(t2, np.exp(-t2) * np.sin(2 * np.pi * t2), 'rs-.')

plt.xlabel('time')
plt.ylabel('volts')
plt.title('Damped oscillation')
plt.show()

import plotly as py
import plotly.tools as tls
import plotly.graph_objects as go

py.offline.iplot_mpl(fig1)

fig = tls.mpl_to_plotly(fig1)

fig['layout'] = {'title': 'Damped oscillation',
               'xaxis': {'anchor': 'y', 'domain': [0.0, 1.0], 'title': 'time'},
               'yaxis': {'anchor': 'x', 'domain': [0.0, 1.0], 'title': 'volts'}}

fig['layout'].update(showlegend=True, autosize=True, template= None)
py.offline.iplot(fig)