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Line chart to surface chart

[UPDATE: Sorry for not providing the piece where the author of the codes create example data. I have updated the codes]
I found an example of a 3D mesh line chart that satisfied what I need (colouring change with level on z dimension). However, instead of line, I want surface plot. How can I change the codes to have the 3d surface plot?
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from matplotlib import animation, rc
from matplotlib.cm import get_cmap
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.font_manager import FontProperties
from matplotlib.collections import LineCollection
from matplotlib.colors import ListedColormap
from mpl_toolkits.mplot3d.art3d import Line3DCollection
index_returns = np.random.normal(loc=1e-4, scale=5e-3, size=(783, 9))
index_returns = np.vstack((np.zeros(shape=(1, 9)) + 100, index_returns))
index_prices = np.cumprod(1 + index_returns, axis=0)
window = 261
df = np.zeros(shape=(index_prices.shape[0]-window, 9))
for i in range(window, index_prices.shape[0], 1):
df[i-window] = (index_prices[i]/index_prices[i-window]) - 1
index = pd.date_range('2019-01-01', periods=index_prices.shape[0]-window, freq='B')
columns = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I']
df = pd.DataFrame(df, index=index, columns=columns)
# create the figure
fig = plt.figure(figsize=(14.4, 9))
ax = fig.add_subplot(111, projection='3d')
fig.patch.set_alpha(1)
# get the cmap to use
cmap = get_cmap('RdYlGn')
# get the slice based on data frame
current_slice = df.values[:261, :]
index_names = df.columns
index_dates = df.index
# list holding the lines
lines = []
# for each index...
for i in range(current_slice.shape[1]):
# get the coordinates
x = np.array(np.arange(current_slice.shape[0]))
y = np.tile(i, current_slice.shape[0])
z = np.array(current_slice[:, i])
# crete points and segments to color
points = np.array([x, y, z]).T.reshape(-1, 1, 3)
segments = np.concatenate([points[:-1], points[1:]], axis=1)
# Create a continuous norm to map from data points to colors
norm = plt.Normalize(-0.19, 0.19)
lc = Line3DCollection(segments, cmap=cmap, norm=norm, zorder=current_slice.shape[1]-i)
# Set the values used for colormapping
lc.set_array(z)
lc.set_linewidth(2)
lc.set_color(cmap(z[-1] * 2.5 + 0.5))
lc.set_label(index_names[i])
lines.append(ax.add_collection(lc))
# add the grids
ax.legend(loc='center right', bbox_to_anchor=(1.1, 0.46), fancybox=True, facecolor=(.95,.95,.95,1), framealpha=1, shadow=False, frameon=True, ncol=1, columnspacing=0, prop={'family': 'DejaVu Sans Mono'})
ax.set_zlabel('Rolling Equity 1Y', labelpad=10)
ax.set_zlim(-0.39, 0.39)
ax.set_zticklabels([' '* 3 + '{:.0%}'.format(val) for val in ax.get_zticks()], fontdict={'verticalalignment': 'center', 'horizontalalignment': 'center'})
ax.set_xlabel('Date', labelpad=30)
ax.set_xlim(0, current_slice.shape[0]-1)
ax.set_xticklabels([index_dates[int(val)].strftime('%m/%y') for val in ax.get_xticks()[:-1]] + [''], rotation=0, fontdict={'verticalalignment': 'top', 'horizontalalignment': 'center'})
ax.set_yticks(np.arange(current_slice.shape[1]))
ax.set_yticklabels([index_names[i] for i in range(current_slice.shape[1])], rotation=-15, fontdict={'verticalalignment': 'center', 'horizontalalignment': 'left'})
# show the plot
plt.show()

How to add logo to below of the x axis in the matplotlib charts

I want to add logo to the bottom right of the chart using matplotlib.
My logo is not fitting in the proper position.
my logo source="https://raw.githubusercontent.com/cldougl/plot_images/add_r_img/vox.png"
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as image
import matplotlib.pyplot as plt#
from matplotlib.offsetbox import OffsetImage
fig, ax = plt.subplots()
logo=image.imread("https://raw.githubusercontent.com/cldougl/plot_images/add_r_img/vox.png")
# You have to add your own logo, this is in my own folder
addLogo = OffsetImage(logo, zoom=0.4)
#addLogo.set_zorder(100)
addLogo.set_offset((250,-25)) # pass the position in a tuple
ax.add_artist(addLogo)
height = [6, 10, 5, 18, 45]
bars = ('A', 'B', 'C', 'D', 'E')
y = np.arange(len(bars))
plt.bar(y, height, color=(0.2, 0.4, 0.6, 0.6))
In jupyter notebook logo is like mirror.

Missing labels in matplotlib pie chart

I try to plot a pie chart using Python 3 Matplotlib v2.2.2-4build1 on Ubuntu 18.10. Everything seems to be ok except labels - they are missing. Tried to add it according to official documentation (https://matplotlib.org/api/_as_gen/matplotlib.pyplot.pie.html), tried to use an example from the web (https://pythonspot.com/matplotlib-pie-chart/) - same result, no labels.
Here is a simplified version of my code:
import numpy as np
import matplotlib.pyplot as plt
import sys
headers = ['a', 'b', 'c', 'd', 'e']
values = [5, 4, 3, 2, 1]
sum = sum(values)
labels = []
for v in values:
labels.append('{:.1f}%'.format(100 * v / sum))
fig, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal"))
wedges, texts = ax.pie(values, labels=labels, textprops=dict(color="w"))
plt.show()
Here is what I see - no labels:
Tried to use a tuple instead of a list - same thing.
Could anybody help me?

You might want to make the color of your labels non-white on a white background :)
Also using sum as a variable name overwrites the function, so your're better off choosing something else.
import numpy as np
import matplotlib.pyplot as plt
import sys
headers = ['a', 'b', 'c', 'd', 'e']
values = [5, 4, 3, 2, 1]
sumT = sum(values)
labels = []
for v in values:
labels.append('{:.1f}%'.format(100 * v / sumT))
fig, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal"))
wedges, texts = ax.pie(values, labels=labels, textprops=dict(color="k"))
plt.show()
Or if you want the labels to be inside:
import numpy as np
import matplotlib.pyplot as plt
import sys
def func(pct, allvals):
absolute = int(pct/100.*sum(allvals))
return "{:.1f}%)".format(pct)
headers = ['a', 'b', 'c', 'd', 'e']
values = [5, 4, 3, 2, 1]
sumT = sum(values)
labels = []
for v in values:
labels.append('{:.1f}%'.format(100 * v / sumT))
fig, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal"))
wedges, texts = ax.pie(values, autopct=lambda pct: func(pct,
values), textprops=dict(color="w"))
plt.show()

import numpy as np
import matplotlib.pyplot as plt
import sys
headers = ['a', 'b', 'c', 'd', 'e']
values = [5, 4, 3, 2, 1]
colors=['yellow','blue','red','pink','green']
plt.pie(values,labels=headers,
colors=colors,autopct='%1.2f%%',
shadow=True,startangle=90)
plt.title('pie chart')
plt.show()

Adding the plt.legend() statement before the plt.show() will do the job.
import numpy as np
import matplotlib.pyplot as plt
import sys
headers = ['a', 'b', 'c', 'd', 'e']
values = [5, 4, 3, 2, 1]
labels = []
for v in values:
labels.append('{:.1f}%'.format(100 * v / sum))
fig, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal"))
wedges, texts = ax.pie(values, labels=labels, textprops=dict(color="w"))
plt.legend()
plt.show()

How to change the text color of font in legend?

Is there a way to change the font color of the legend in a matplotlib plot?
Specially in occasions where the background of the plot is dark, the default black text in the legend is hard or impossible to read.

call Legend.get_texts() will get a list of Text object in the legend object:
import pylab as pl
pl.plot(randn(100), label="randn")
l = legend()
for text in l.get_texts():
text.set_color("red")

As of matplotlib version 3.3.0, you can now directly use the keyword argument labelcolor in matplotlib.pyplot.legend().
Example using the same color as the corresponding artist by setting labelcolor='linecolor':
import matplotlib.pyplot as plt
import numpy as np
plt.figure(figsize=(4, 3))
plt.plot(np.arange(10), np.random.rand(10) * 0, '-', label='spam')
plt.plot(np.arange(10), np.random.rand(10) * 1, ':', label='ham')
plt.plot(np.arange(10), np.random.rand(10) * 2, 'o', label='eggs')
plt.legend(labelcolor='linecolor')
Example changing all text to white by setting labelcolor='w', e.g. for dark backgrounds:
import matplotlib.pyplot as plt
import numpy as np
plt.figure(figsize=(4, 3))
plt.plot(np.arange(10), np.random.rand(10) * 0, '-', label='spam')
plt.plot(np.arange(10), np.random.rand(10) * 1, ':', label='ham')
plt.plot(np.arange(10), np.random.rand(10) * 2, 'o', label='eggs')
plt.legend(facecolor='k', labelcolor='w')

Because plt.setp broadcasts over iterables, you can also modify the text color in one line:
# Show some cool graphs
legend = plt.legend()
plt.setp(legend.get_texts(), color='w')
The last line will apply the colour to all elements in the collection of texts.

You can also do it with setp():
import pylab as plt
leg = plt.legend(framealpha = 0, loc = 'best')
for text in leg.get_texts():
plt.setp(text, color = 'w')
this method also allows you to set the fontsize and any number of other font properties in one line (listed here: http://matplotlib.org/users/text_props.html)
full example:
import pylab as plt
x = range(100)
y1 = range(100,200)
y2 = range(50,150)
fig = plt.figure(facecolor = 'k')
ax = fig.add_subplot(111, axisbg = 'k')
ax.tick_params(color='w', labelcolor='w')
for spine in ax.spines.values():
spine.set_edgecolor('w')
ax.plot(x, y1, c = 'w', label = 'y1')
ax.plot(x, y2, c = 'g', label = 'y2')
leg = plt.legend(framealpha = 0, loc = 'best')
for text in leg.get_texts():
plt.setp(text, color = 'w')
plt.show()

Anyone looking to change the color of the TITLE of the legend; seems to only be available through the side door:
leg._legend_title_box._text.set_color('#FFFFFF')

matplotlib: using a colormap to color table-cell background

I have a Pandas dataframe, and i want to plot it as matplotlib table. So far i have that part working with following code:
import numpy as np
randn = np.random.randn
from pandas import *
idx = Index(arange(1,11))
df = DataFrame(randn(10, 5), index=idx, columns=['A', 'B', 'C', 'D', 'E'])
vals = np.around(df.values,2)
fig = plt.figure(figsize=(15,8))
ax = fig.add_subplot(111, frameon=True, xticks=[], yticks=[])
the_table=plt.table(cellText=vals, rowLabels=df.index, colLabels=df.columns,
colWidths = [0.03]*vals.shape[1], loc='center')
table_props = the_table.properties()
table_cells = table_props['child_artists']
clm = cm.hot(vals)
for cell in table_cells:
cell.set_height(0.04)
# now i would like to set the backgroundcolor of the cell
At the end of this i would like to set the background-color of the cell according to the colormap - but how do i look it up in the clm array without an index?
Another question: can i somehow pass a format string to the table, so that it formats the text to 2 decimal places?
Any hints appreciated,
Andy

You can use plt.Normalize() to normalize your data, and the pass the normalized data to a Colormap object, for example plt.cm.hot().
plt.table() has an argument cellColours, which will be used to set the cells' background color accordingly.
Because cm.hot maps black to the minimal value, I increased the value range when creating the normalization object.
Here is the code:
from matplotlib import pyplot as plt
import numpy as np
randn = np.random.randn
from pandas import *
idx = Index(np.arange(1,11))
df = DataFrame(randn(10, 5), index=idx, columns=['A', 'B', 'C', 'D', 'E'])
vals = np.around(df.values,2)
norm = plt.Normalize(vals.min()-1, vals.max()+1)
colours = plt.cm.hot(normal(vals))
fig = plt.figure(figsize=(15,8))
ax = fig.add_subplot(111, frameon=True, xticks=[], yticks=[])
the_table=plt.table(cellText=vals, rowLabels=df.index, colLabels=df.columns,
colWidths = [0.03]*vals.shape[1], loc='center',
cellColours=colours)
plt.show()

The Andy's code working:
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# sudo apt-get install python-pandas
# sudo apt-get install python-matplotlib
#
# python teste.py
from matplotlib import pyplot
from matplotlib import cm
import numpy
from pandas import *
idx = Index(numpy.arange(1, 11))
df = DataFrame(
numpy.random.randn(10, 5),
index=idx,
columns=['A', 'B', 'C', 'D', 'E']
)
vals = numpy.around(df.values, 2)
normal = pyplot.normalize(vals.min()-1, vals.max()+1)
fig = pyplot.figure(figsize=(15, 8))
ax = fig.add_subplot(111, frameon=True, xticks=[], yticks=[])
the_table = pyplot.table(
cellText=vals,
rowLabels=df.index,
colLabels=df.columns,
colWidths = [0.03]*vals.shape[1],
loc='center',
cellColours=pyplot.cm.hot(normal(vals))
)
pyplot.show()