I am trying to plot the no of pending and declined applications by month.
I am having 2 difficulties.
1.My values on Z axis don match with the values in 'dz' list. For example, if you check the array 'z0', the no.of pending applications is 82 for December. But in the plot you can see that the highest value is below 82 against December. Similarly,Jan has 31 pending but when plotted the value is well below it.This variation exists for all the values plotted.
2.I have many zeros in the list. I would like to add a different color(say transparent) and hide the appearance of zero values in the plot. This is to ensure my plot is clear and I see actual values. I am not sure how to do it inside the for loop as I am stacking values.
import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime,date
import calendar
from itertools import cycle, islice
#from mpl_toolkits.mplot3d import Axes3D
from mpl_toolkits.mplot3d import axes3d
import numpy as np
# Set plotting style
plt.style.use('seaborn-white')
dz=[]
z0 = np.array([ 31., 23., 11., 8., 7., 6., 6., 6., 5., 4.,
3., 1., 0., 21., 13., 7., 4., 3., 3., 3.,
3., 1., 0., 0., 0., 0., 22., 11., 4., 2.,
1., 1., 0., 0., 0., 0., 0., 0., 0., 38.,
26., 16., 15., 9., 8., 6., 4., 2., 0., 0.,
0., 0., 47., 26., 21., 11., 9., 7., 6., 4.,
0., 0., 0., 0., 0., 51., 31., 17., 14., 9.,
6., 5., 0., 0., 0., 0., 0., 0., 33., 25.,
14., 4., 4., 4., 0., 0., 0., 0., 0., 0.,
0., 35., 24., 14., 9., 5., 0., 0., 0., 0.,
0., 0., 0., 0., 72., 55., 41., 20., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 50., 27., 15.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
77., 44., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 82.])
dz.append(z0)
z1 =[ 14., 5., 8., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 13., 7., 2., 1., 1., 0., 0., 0., 0.,
0., 0., 0., 0., 14., 8., 4., 0., 1., 0., 0.,
0., 0., 0., 0., 0., 0., 19., 3., 5., 0., 2.,
0., 0., 0., 0., 0., 0., 0., 0., 11., 13., 3.,
3., 0., 0., 0., 0., 0., 0., 0., 0., 0., 19.,
10., 3., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
0., 13., 2., 1., 0., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 10., 2., 0., 0., 0., 0., 0., 0.,
0., 0., 0., 0., 0., 11., 1., 3., 0., 0., 0.,
0., 0., 0., 0., 0., 0., 0., 14., 0., 1., 0.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 12., 3.,
0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
15.]
dz.append(z1)
_zpos = z0*0
xlabels = pd.Index(['01', '02', '03', '04', '05', '06', '07', '08', '09',
'10', '11', '12'], dtype='object', name='dates')
ylabels = pd.Index(['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug',
'Sep', 'Oct', 'Nov', 'Dec'], dtype='object',
name='Month')
x = np.arange(xlabels.shape[0])
y = np.arange(ylabels.shape[0])
x_M, y_M = np.meshgrid(x, y, copy=False)
fig = plt.figure(figsize=(15, 15))
ax = fig.add_subplot(111, projection='3d')
# Making the intervals in the axes match with their respective entries
ax.w_xaxis.set_ticks(x + 0.5/2.)
ax.w_yaxis.set_ticks(y + 0.5/2.)
# Renaming the ticks as they were before
ax.w_xaxis.set_ticklabels(xlabels)
ax.w_yaxis.set_ticklabels(ylabels)
# Labeling the 3 dimensions
ax.set_xlabel('Months Taken')
ax.set_ylabel('Month created')
ax.set_zlabel('Count')
# Choosing the range of values to be extended in the set colormap
values = np.linspace(0.2, 1., x_M.ravel().shape[0])
# Selecting an appropriate colormap
colors = ['#FFC04C', '#ee2f2f', '#3e9a19',
'#599be5','#bf666f','#a235bf','#848381','#fb90d6','#fb9125']
for i in range(2):
ax.bar3d(x_M.ravel(), y_M.ravel(), _zpos, dx=0.3, dy=0.3, dz=dz[i],
color=colors[i])
_zpos += dz[i]
#plt.gca().invert_xaxis()
#plt.gca().invert_yaxis()
Pending_proxy = plt.Rectangle((0, 0), 1, 1, fc="#FFC04C90")
Declined_proxy = plt.Rectangle((0, 0), 1, 1, fc="#ee2f2f90")
ax.legend([Pending_proxy,
Declined_proxy],['Pending',
'Declined',
])
plt.show()
