We Keep Coding

Finding average of multiple lines in matplotlib

I am trying to create a graph that takes the averages from the below lines and plot them on the same new graph of the same nature.
fig, ax = plt.subplots(1,1, figsize=(10,12))
yticks = np.arange(nchan) * 0.2
lines_BC = plt.plot(resampled_BC.T + yticks[np.newaxis], label = "BC", c='black')
lines_CP = plt.plot(resampled_CP.T + yticks[np.newaxis], label = "CP", c='red')
lines_CR = plt.plot(resampled_CR.T + yticks[np.newaxis], label = "CR", c='cyan')
lines_DC = plt.plot(resampled_DC.T + yticks[np.newaxis], label = "DC", c='blue')
lines_JC = plt.plot(resampled_JC.T + yticks[np.newaxis], label = "JC", c='lime')
ax.set_yticks(yticks)
ax.set_yticklabels(muscles)
ax.set_ylabel('Muscles')
ax.set_xlabel('Time (ms)')
leg = ax.legend([lines_BC[0]] + [lines_CP[0]] + [lines_CR[0]] + [lines_DC[0]] + [lines_JC[0]], ['BC', 'CP', 'CR', 'DC', 'JC'], loc='upper right')
plt.show()
I have tried using np.mean but to no luck.

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

ax.text2d in python (Matplotlib)

I am using text2d() to write some information on the bar3d-Diagram.
The piece of code is this one:
textstr = '\n'.join((
'{}'.format(langbezeichnung),
'Beprobung {} - {}'.format(datum_start, datum_end),
'{} Messstellen'.format(anzahl_mst_para),
"BG = {} µg/L".format(bestimmungsgrenze),
"75% SW = {} µg/L".format(warnwert),
"SW = {} µg/L".format(grenzwert)))
ax.text2D(0.645, 0.74, s=textstr, transform=ax.transAxes, fontsize=12, ha='left', va='top', bbox=dict(facecolor='white', alpha=1, edgecolor='black', linewidth=0.2, boxstyle='square'))
and the result is like that:
but i would like to have the equal signs ("=") at the same line.
Could anybody help me?
Thank you
Rabea

Use Monospace font and set the space. The spaces will align in this case. Example...
ax = plt.axes(projection='3d')
textstr = '\n'.join((
'{}'.format('langbezeichnung'),
'Beprobung {} - {}'.format('datum_start', 'datum_end'),
'{} Messstellen'.format('anzahl_mst_para'),
"BG = {} µg/L".format('bestimmungsgrenze'),
"75% SW = {} µg/L".format('warnwert'),
"SW = {} µg/L".format('grenzwert')))
ax.text2D(0.645, 0.74, s=textstr, family='monospace', transform=ax.transAxes, fontsize=12, ha='left', va='top', bbox=dict(facecolor='white', alpha=1, edgecolor='black', linewidth=0.2, boxstyle='square'))

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()

Bar chart starting out of axis in python

I need to copy the bar chart in the image with python.
bar chart I have to copy
What I have been able to achieve is next image.
bar chart I have achieved
And the code I have used is:
import matplotlib.pyplot as plt
ausgaben = 130386
einnahmen = 147233
profit = einnahmen-ausgaben
titles = ["Ausgaben", "Profit", "Einnahmen"]
euros = [ausgaben, profit, einnahmen]
colors = ['#6F8CA7', '#F6BC06', '#59908F']
dummysum1 = []
dummysum2 = []
for i in range(len(euros)):
dummysum1.append(euros[i]+4000)
dummysum2.append(max(euros)+15000)
if euros[1] > 0:
dummysum1[1] = euros[1]+4000
if euros[1] <= 0:
dummysum1[1] = 4000
position1 = (euros[0]+euros[2])/2
percentile = (euros[2]-euros[0])/euros[0]*100
if percentile > 0:
label0 = '+{:.1f}%'.format(percentile)
else:
label0 = '{:.1f}%'.format(percentile)
fig, ax = plt.subplots(figsize=(7, 5))
fig.set_facecolor('#D0A210')
fig.patch.set_alpha(0.2)
ax.bar(titles[0], euros[0], alpha=0.6, color=colors[0])
ax.bar(titles[1], euros[1], alpha=0.6, color=colors[1])
ax.bar(titles[2], euros[2], alpha=0.6, color=colors[2])
plt.axhline(y=euros[0], color='#BCBCBC')
plt.axhline(y=euros[2], color='#BCBCBC')
ax.set_facecolor('#D0A210')
ax.patch.set_alpha(0.02)
ax.xaxis.set_visible(False)
ax.yaxis.set_visible(False)
ax.spines.right.set_visible(False)
ax.spines.left.set_visible(False)
ax.spines.top.set_visible(False)
ax.spines.bottom.set_visible(False)
ax.text(titles[0], dummysum1[0], '{} €'.format(euros[0]), horizontalalignment='center')
ax.text(titles[1], dummysum1[1], '{} €'.format(euros[1]), horizontalalignment='center')
ax.text(titles[2], dummysum1[2], '{} €'.format(euros[2]), horizontalalignment='center')
ax.text(2.58, position1-1000, label0)
ax.text(titles[0], dummysum2[0], titles[0], horizontalalignment='center')
ax.text(titles[1], dummysum2[1], titles[1], horizontalalignment='center')
ax.text(titles[2], dummysum2[2], titles[2], horizontalalignment='center')
plt.show()
. How can I get the yellow bar chart starting at y=130386 instead of y=0 and the yellow arrow at the right hand side?
(The first question is the most important!)
Thank you all!

For the first question, just add a value for the bottom parameter. I have also added the arrow using annotate:
import matplotlib.pyplot as plt
ausgaben = 130386
einnahmen = 147233
profit = einnahmen-ausgaben
titles = ["Ausgaben", "Profit", "Einnahmen"]
euros = [ausgaben, profit, einnahmen]
colors = ['#6F8CA7', '#F6BC06', '#59908F']
dummysum1 = []
dummysum2 = []
for i in range(len(euros)):
dummysum1.append(euros[i]+4000)
dummysum2.append(max(euros)+15000)
if euros[1] > 0:
dummysum1[1] = euros[1]+4000
if euros[1] <= 0:
dummysum1[1] = 4000
position1 = (euros[0]+euros[2])/2
percentile = (euros[2]-euros[0])/euros[0]*100
if percentile > 0:
label0 = '+{:.1f}%'.format(percentile)
else:
label0 = '{:.1f}%'.format(percentile)
fig, ax = plt.subplots(figsize=(7, 5))
fig.set_facecolor('#D0A210')
fig.patch.set_alpha(0.2)
ax.bar(titles[0], euros[0], alpha=0.6, color=colors[0])
ax.bar(titles[1], euros[1], alpha=0.6, color=colors[1], bottom=ausgaben)
ax.bar(titles[2], euros[2], alpha=0.6, color=colors[2])
plt.axhline(y=euros[0], color='#BCBCBC')
plt.axhline(y=euros[2], color='#BCBCBC')
ax.set_facecolor('#D0A210')
ax.patch.set_alpha(0.02)
ax.xaxis.set_visible(False)
ax.yaxis.set_visible(False)
ax.spines.right.set_visible(False)
ax.spines.left.set_visible(False)
ax.spines.top.set_visible(False)
ax.spines.bottom.set_visible(False)
ax.text(titles[0], dummysum1[0], '{} €'.format(euros[0]), horizontalalignment='center')
ax.text(titles[1], dummysum1[1]+ausgaben, '{} €'.format(euros[1]), horizontalalignment='center')
ax.text(titles[2], dummysum1[2], '{} €'.format(euros[2]), horizontalalignment='center')
ax.text(2.58, position1-1000, label0)
ax.text(titles[0], dummysum2[0], titles[0], horizontalalignment='center')
ax.text(titles[1], dummysum2[1], titles[1], horizontalalignment='center')
ax.text(titles[2], dummysum2[2], titles[2], horizontalalignment='center')
ax.annotate("", xy=(2.5, ausgaben+profit*1.05), xytext=(2.5, ausgaben), arrowprops=dict(arrowstyle="->", color="orange", lw=2.0))
plt.show()