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Animated/interactive plots for DBSCAN clustering

I have the code below. I'm trying to build an interactive DBSCAN clustering plot. When I run it, I get three plots but not interactive. Where is the problem in the code and how to fix it.
df_mv = pd.read_csv(r"https://raw.githubusercontent.com/HanaBachi/MachineLearning/main/multishape.csv") # load from Prof. Pyrcz's GitHub
df_mv.head()
text_trap = io.StringIO()
sys.stdout = text_trap
l = widgets.Text(value=' DBSCAN, Hana Bachi, The University of Texas at Austin',
layout=Layout(width='950px', height='30px'))
eps = widgets.FloatSlider(min=0, max = 2, value=0.1, step = 0.1, description = 'eps',orientation='horizontal', style = {'description_width': 'initial'}, continuous_update=False)
minPts = widgets.FloatSlider(min=0, max = 5, value=1, step = 1, description = 'minPts %',orientation='horizontal',style = {'description_width': 'initial'}, continuous_update=False)
color = ['blue','red','green','yellow','orange','white','magenta','cyan']
style = {'description_width': 'initial'}
ui = widgets.HBox([eps,minPts],)
ui2 = widgets.VBox([l,ui],)
# create activation function plots
def DBSCAN_plot(eps, minPts):
db = DBSCAN(eps=0.155, min_samples=5).fit(df_mv)
labels = db.labels_
# n_clusters_ = len(set(labels)) - (1 if -1 in labels else 0)
# x = df_mv.values[:,0]
# y = df_mv.values[:,1]
# cmap = plt.cm.rainbow
#norm = mc.BoundaryNorm(labels, cmap.N)
plt.figure(figsize=(14,7))
plt.scatter(x, y, c=labels, cmap='tab10', s=50)
plt.scatter(x[np.where(labels==-1)], y[np.where(labels==-1)], c='k', marker='x', s=100)
plt.title('DBSCAN interactive plot', fontsize = 20)
plt.colorbar()
plt.show()
plt.subplots_adjust(left=0.0, bottom=0.0, right=2.0, top=1.0, wspace=0.2, hspace=0.3)
plt.show()
# create dashboard/formatting
uia = widgets.HBox([interactive_plot1],)
uia2 = widgets.VBox([eps, uia],)
uib = widgets.HBox([interactive_plot1],)
uib2 = widgets.VBox([minPts, uib],)
interactive_plot1 = widgets.interactive_output(DBSCAN_plot, {'eps': eps,'minPts':minPts})
interactive_plot1.clear_output(wait = True) #
How can I make this plot interactive in function of eps and minPts

Barplot subplot legend python

Hello everyone how can i make legend for 3 different bar color that code with subplot?
Data frame:
This is my code:
fig,axs = plt.subplots(2,3, figsize=(30,20))
axs[0,1].bar(x = df_7_churn_tenure['Kategori'],height = df_7_churn_tenure['Jumlah Churn'],color = ['lightsalmon','maroon','darkorange'])
axs[0,1].legend(['Low Tenure = x<24','Medium Tenure = 24<= x <=48','High Tenure = x >=48'],loc='best',fontsize=12)
plt.show()
And the result for barplot legend only shows 1 label like this:
Is there any solution to shows all of my legend?

Try this:
fig,axs = plt.subplots(2,3, figsize=(30,20))
axs[0,1].bar(x = df_7_churn_tenure['Kategori'],height = df_7_churn_tenure['Jumlah Churn'],color ['lightsalmon','maroon','darkorange'])
axs = axs[0,1]
lns1 = axs.plot('-',label = 'Low Tenure = x<24')
lns2 = axs.plot('-',label = 'Medium Tenure = 24<= x <=48')
lns3 = axs.plot('-',label = 'High Tenure = x >=48')
# added these three lines
lns = lns1+lns2+lns3
labs = [l.get_label() for l in lns]
axs.legend(lns, labs,loc=0)
plt.show()

Bokeh how to get GlyphRenderer for Annotation

With Bokeh, how do I get a handle to the Renderer (or GlyphRenderer) for an Annotation? Is this possible?
I would like to be able to toggle a Band (which is an Annotation) on and off with an interactive legend, so I need to be able to pass a list of Renderers to the LegendItem constructor.
This code:
maxline = fig.line(x='Date', y=stn_max, line_width=0.5, legend=stn_max, name="{}_line".format(stn_max), color=stn_color, alpha=0.75, source=source)
minline = fig.line(x='Date', y=stn_min, line_width=0.5, legend=stn_min, name="{}_line".format(stn_min), color=stn_color, alpha=0.75, source=source)
band = bkm.Band(base='Date', lower=stn_min, upper=stn_max, fill_alpha=0.50, line_width=0.5, fill_color=stn_color, source=source)
bkm.LegendItem(label=stn, renderers=[maxline, minline, band])
Produces this error
...
ValueError: expected an element of List(Instance(GlyphRenderer)), got seq with invalid items [Band(id='1091', ...)]

For LegendItem only instances of GlyphRenderer can be passed to its renderers attribute and Band is not based on GlyphRenderer so it gives error. In the code below the Band visibility is being toggled by means of a callback:
from bokeh.plotting import figure, show
from bokeh.models import Band, ColumnDataSource, Legend, LegendItem, CustomJS
import pandas as pd
import numpy as np
x = np.random.random(2500) * 140 - 20
y = np.random.normal(size = 2500) * 2 + 5
df = pd.DataFrame(data = dict(x = x, y = y)).sort_values(by = "x")
sem = lambda x: x.std() / np.sqrt(x.size)
df2 = df.y.rolling(window = 100).agg({"y_mean": np.mean, "y_std": np.std, "y_sem": sem})
df2 = df2.fillna(method = 'bfill')
df = pd.concat([df, df2], axis = 1)
df['lower'] = df.y_mean - df.y_std
df['upper'] = df.y_mean + df.y_std
source = ColumnDataSource(df.reset_index())
p = figure(tools = "pan,wheel_zoom,box_zoom,reset,save")
scatter = p.scatter(x = 'x', y = 'y', line_color = None, fill_alpha = 0.3, size = 5, source = source)
band = Band(base = 'x', lower = 'lower', upper = 'upper', source = source)
p.add_layout(band)
p.title.text = "Rolling Standard Deviation"
p.xaxis.axis_label = 'X'
p.yaxis.axis_label = 'Y'
callback = CustomJS(args = dict(band = band), code = """
if (band.visible == false)
band.visible = true;
else
band.visible = false; """)
legend = Legend(items = [ LegendItem(label = "x", renderers = [scatter, band.source.selection_policy]) ])
legend.click_policy = 'hide'
scatter.js_on_change('visible', callback)
p.add_layout(legend)
show(p)
Result:

subplot with plotly with multiple traces

i am trying to create subplots for the following plots:
the code i used for the the plots are :
radius_mean1 = df[df['diagnosis']==1]['radius_mean']
radius_mean0 = df[df['diagnosis']==0]['radius_mean']
trace_rm1 = go.Histogram(x = radius_mean1, opacity = 0.75, name = 'malignant')
trace_rm2 = go.Histogram(x = radius_mean0, opacity = 0.75, name = 'benign')
data2 = [trace_rm1,trace_rm2]
layout2 = go.Layout(barmode = 'overlay', title = 'radius mean')
fig2 = go.Figure(data=data2, layout=layout2)
py.iplot(fig2)
and similar for the other plot
now i use the following code i found to create subplots:
fig.append_trace(fig1['data'][1], 1, 1)
fig.append_trace(fig2['data'][0], 2, 1)
py.iplot(fig)
and i get this :
how do i add both benign and malignant results to the subplots ?
i cant seem to edit the [0] or [ 1] to show both ie have the first 2 plots exactly into my subplot showing both malignant and benign and not just one or the other.

The data here is not complete, so I using some demo data to present.
import numpy as np
import plotly.graph_objs as go
import plotly
a = np.random.normal(0,1,100)
b = np.random.normal(-2,5,100)
c = np.random.normal(0,1,100)
d = np.random.normal(-2,5,100)
fig = plotly.tools.make_subplots(rows=2,cols=1)
trace_rm1 = go.Histogram(x = a, opacity = 0.75, name = 'malignant')
trace_rm2 = go.Histogram(x = b, opacity = 0.75, name = 'benign')
fig.append_trace(go.Histogram(x = a, opacity = 0.75, name = 'benign'),1,1)
fig.append_trace(go.Histogram(x = b, opacity = 0.75, name = 'malignant'),1,1)
fig.append_trace(go.Histogram(x = c, opacity = 0.75, name = 'benign'),2,1)
fig.append_trace(go.Histogram(x = d, opacity = 0.75, name = 'malignant'),2,1)
fig.layout.update(go.Layout(barmode = 'overlay',))
plotly.offline.plot(fig)

Basemap causing data to not plot

I am getting a very strange error using basemap. No error appears, yet my 3rd plot has no data plotted when data does indeed exist. Below is my code. When run, you will see that both modis and seawifs data is plotted, but viirs is not. I can't figure out why.
import numpy as np
import urllib
import urllib2
import netCDF4
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
from datetime import datetime, date, time, timedelta
import json
import math
def indexsearch(datebroken,year, month, day):
for i in range(0,len(datebroken)):
if (datebroken[i,0] == year and datebroken[i,1] == month and datebroken[i,2] == day):
return i
url = 'http://coastwatch.pfeg.noaa.gov/erddap/griddap/erdMWchlamday.nc?chlorophyll' +\
'[(2002-07-16T12:00:00Z):1:(2015-04-16T00:00:00Z)][(0.0):1:(0.0)][(36):1:(39)][(235):1:(240)]'
file = 'erdMWchlamday.nc'
urllib.urlretrieve(url, file)
ncfilemod = netCDF4.Dataset(file)
ncv1 = ncfilemod.variables
print ncv1.keys()
time1=ncv1['time'][:]
inceptiondate = datetime(1970, 1, 1, 0, 0, 0)
timenew1=[]
for i in time1[:]:
newdate = inceptiondate + timedelta(seconds=i)
timenew1.append(newdate.strftime('%Y%m%d%H'))
datebroken1 = np.zeros((len(timenew1),4),dtype=int)
for i in range(0,len(timenew1)):
datebroken1[i,0] = int(timenew1[i][0:4])
datebroken1[i,1] = int(timenew1[i][4:6])
datebroken1[i,2] = int(timenew1[i][6:8])
datebroken1[i,3] = int(timenew1[i][8:10])
lon1= ncv1['longitude'][:]
lat1 = ncv1['latitude'][:]
lons1, lats1 = np.meshgrid(lon1,lat1)
chla1 = ncv1['chlorophyll'][:,0,:,:]
url = 'http://coastwatch.pfeg.noaa.gov/erddap/griddap/erdSWchlamday.nc?chlorophyll' +\
'[(1997-09-16):1:(2010-12-16T12:00:00Z)][(0.0):1:(0.0)][(36):1:(39)][(235):1:(240)]'
file = 'erdSWchlamday.nc'
urllib.urlretrieve(url, file)
#Ncfile 2
ncfilewif = netCDF4.Dataset(file)
ncv2 = ncfilewif.variables
print ncv2.keys()
time2=ncv2['time'][:]
inceptiondate = datetime(1970, 1, 1, 0, 0, 0)
timenew2=[]
for i in time2[:]:
newdate = inceptiondate + timedelta(seconds=i)
timenew2.append(newdate.strftime('%Y%m%d%H'))
datebroken2 = np.zeros((len(timenew2),4),dtype=int)
for i in range(0,len(timenew2)):
datebroken2[i,0] = int(timenew2[i][0:4])
datebroken2[i,1] = int(timenew2[i][4:6])
datebroken2[i,2] = int(timenew2[i][6:8])
datebroken2[i,3] = int(timenew2[i][8:10])
lon2= ncv2['longitude'][:]
lat2 = ncv2['latitude'][:]
lons2, lats2 = np.meshgrid(lon2,lat2)
chla2 = ncv2['chlorophyll'][:,0,:,:]
url = 'http://coastwatch.pfeg.noaa.gov/erddap/griddap/erdVH2chlamday.nc?chla' +\
'[(2012-01-15):1:(2015-05-15T00:00:00Z)][(39):1:(36)][(-125):1:(-120)]'
file = 'erdVH2chlamday.nc'
urllib.urlretrieve(url, file)
ncfileviir = netCDF4.Dataset(file)
ncv3 = ncfileviir.variables
print ncv3.keys()
time3=ncv3['time'][:]
inceptiondate = datetime(1970, 1, 1, 0, 0, 0)
timenew3=[]
for i in time3[:]:
newdate = inceptiondate + timedelta(seconds=i)
timenew3.append(newdate.strftime('%Y%m%d%H'))
datebroken3 = np.zeros((len(timenew3),4),dtype=int)
for i in range(0,len(timenew3)):
datebroken3[i,0] = int(timenew3[i][0:4])
datebroken3[i,1] = int(timenew3[i][4:6])
datebroken3[i,2] = int(timenew3[i][6:8])
datebroken3[i,3] = int(timenew3[i][8:10])
lon3= ncv3['longitude'][:]
lat3 = ncv3['latitude'][:]
lons3, lats3 = np.meshgrid(lon3,lat3)
chla3 = ncv3['chla'][:,:,:]
i1=indexsearch(datebroken1,2012,6,16)
print i1
i2=indexsearch(datebroken2,2010,6,16)
print i2
i3=indexsearch(datebroken3,2012,6,15)
print i3
chla1plot = chla1[i1,:,:]
chla2plot = chla2[i2,:,:]
chla3plot = chla3[i3,:,:]
ncfileviir.close()
ncfilemod.close()
ncfilewif.close()
Important code is below here. All code above is just pulling the data into python to plot.
minlat = 36
maxlat = 39
minlon = 235
maxlon = 240
# Create map
fig = plt.figure()
#####################################################################################################################
#plot figure 1
ax1 = fig.add_subplot(221)
m = Basemap(projection='merc', llcrnrlat=minlat,urcrnrlat=maxlat,llcrnrlon=minlon, urcrnrlon=maxlon,resolution='h')
cs1 = m.pcolormesh(lons1,lats1,chla1plot,cmap=plt.cm.jet,latlon=True)
m.drawcoastlines()
m.drawmapboundary()
m.fillcontinents()
m.drawcountries()
m.drawstates()
m.drawrivers()
#Sets up parallels and meridians.
parallels = np.arange(36.,39,1.)
# labels = [left,right,top,bottom]
m.drawparallels(parallels,labels=[False,True,True,False])
meridians = np.arange(235.,240.,1.)
m.drawmeridians(meridians,labels=[True,False,False,True])
ax1.set_title('Modis')
#####################################################################################################################
#plot figure 2
ax2 = fig.add_subplot(222)
cs2 = m.pcolormesh(lons2,lats2,chla2plot,cmap=plt.cm.jet,latlon=True)
m.drawcoastlines()
m.drawmapboundary()
m.fillcontinents()
m.drawcountries()
m.drawstates()
m.drawrivers()
#Sets up parallels and meridians.
parallels = np.arange(36.,39,1.)
# labels = [left,right,top,bottom]
m.drawparallels(parallels,labels=[False,True,True,False])
meridians = np.arange(235.,240.,1.)
m.drawmeridians(meridians,labels=[True,False,False,True])
ax2.set_title('SeaWIFS')
#####################################################################################################################
#plot figure 3
ax3 = fig.add_subplot(223)
cs3 = m.pcolormesh(lons3,np.flipud(lats3),np.flipud(chla3plot),cmap=plt.cm.jet,latlon=True)
m.drawcoastlines()
m.drawmapboundary()
m.fillcontinents()
m.drawcountries()
m.drawstates()
m.drawrivers()
#Sets up parallels and meridians.
parallels = np.arange(36.,39,1.)
# labels = [left,right,top,bottom]
m.drawparallels(parallels,labels=[False,True,True,False])
meridians = np.arange(235.,240.,1.)
m.drawmeridians(meridians,labels=[True,False,False,True])
ax3.set_title('VIIRS')
# Save figure (without 'white' borders)
#plt.savefig('SSTtest.png', bbox_inches='tight')
plt.show()
My results are shown here!
![results]: http://i.stack.imgur.com/dRjkU.png

The issue that I found was that I had
minlat = 36
maxlat = 39
minlon = 235
maxlon = 240
m = Basemap(projection='merc', llcrnrlat=minlat,urcrnrlat=maxlat,llcrnrlon=minlon, urcrnrlon=maxlon,resolution='h')
The final plot was -125 to -120 which basemap did not automatically handle, but instead placed the plot at an area where I did not have data. I added a new m = basemap statement and changed the meridian numbers for the third graph using -125 to -120 as my longitude and the graph plotted just fine.