I am using matplotlib and a stackedbarchart program for it that someone wrote to graph a stacked bar chart.
My graph:
x-axis has 8 income distributions, one for each bar
y-axis is the % of people in each income distribution. person type-a is the first stack, person type-b is the secon dstack, person type-c is the third stack.
My barchart is center aligned, and I am trying to figure out how to space out the bars so the graph looks better and so the labels are easier to read. Any suggestions, or clarifications?
The program is stackedBarGraph.py and the code looks like this, where widths is an array of 8 values, each corresponding to the width of a bar chart.
Let me know if you need any more information (I tried to keep everything relevant). Thanks!
Full code (I hope it's not too difficult to read):
from __future__ import division
from pylab import *
import seaborn as sns
import pandas as pd
import numpy as np
from stackedbars import StackedBarGrapher
data = csv2rec('coa.csv', delimiter=',')
x = data['totalgrantaid']
y = data['studenteffort']
z = data['parentcontim']
g = data['parentincomeim']
df = pd.DataFrame(dict(grant = x, stud = y, par = z, income = g))
#organize the data to graph
income_brackets = [(0, 25000), (25000, 50000), (50000, 75000), (75000, 100000), (100000, 150000), (150000,200000), (200000,250000), (250000,300000)]
source = {'grant' : [], 'stud': [], 'par': []}
for lower, upper in income_brackets:
for key in source:
source[key].append(median(df.query('income > {} and income < {}'.format(lower, upper))[key]))
#set the widths
source2 = {'grant' : [], 'stud': [], 'par': []}
for lower, upper in income_brackets:
for key in source2:
source2[key].append(pd.DataFrame(df.query('income > {} and income < {}'.format(lower,upper))).count()[key])
total = pd.DataFrame(df.query('income > 0 and income < 300000')['grant']).count()
total = total/10
#graph specifications
d_widths = [(source2['grant'][i]/total)[0] for i in range(8)]
d_colors = ['r','g','b']
d_labels = ('<25000', '25000-\n50000', '50000-\n75000', '75000-\n100000', '100000-\n150000', '150000-\n200000', '200000-\n250000', '250000-\n300000')
d = np.array([[source[k][i] for k in ('grant', 'stud', 'par')] for i in range(8)])
#the graph
fig = plt.figure()
ax1 = fig.add_subplot(111)
mygraph = StackedBarGrapher()
mygraph.stackedBarPlot(ax1,d,d_colors, edgeCols=['#000000']*3,widths = d_widths, showFirst = 8, xLabels=d_labels,scale=True)
Stackedbarchart program:
def stackedBarPlot(self,
ax, # axes to plot onto
data, # data to plot
cols, # colors for each level
xLabels = None, # bar specific labels
yTicks = 6., # information used for making y ticks ["none", <int> or [[tick_pos1, tick_pos2, ... ],[tick_label_1, tick_label2, ...]]
edgeCols=None, # colors for edges
showFirst=-1, # only plot the first <showFirst> bars
scale=False, # scale bars to same height
widths=None, # set widths for each bar
heights=None, # set heights for each bar
ylabel='', # label for x axis
xlabel='' # label for y axis
):
#------------------------------------------------------------------------------
# data fixeratering
# make sure this makes sense
if showFirst != -1:
showFirst = np.min([showFirst, np.shape(data)[0]])
data_copy = np.copy(data[:showFirst]).transpose().astype('float')
data_shape = np.shape(data_copy)
if heights is not None:
heights = heights[:showFirst]
if widths is not None:
widths = widths[:showFirst]
showFirst = -1
else:
data_copy = np.copy(data).transpose()
data_shape = np.shape(data_copy)
# determine the number of bars and corresponding levels from the shape of the data
num_bars = data_shape[1]
levels = data_shape[0]
if widths is None:
widths = np.array([1] * num_bars)
x = np.arange(num_bars)
else:
x = [0]
for i in range(1, len(widths)):
x.append(x[i-1] + (widths[i-1] + widths[i])/2)
# stack the data --
# replace the value in each level by the cumulative sum of all preceding levels
data_stack = np.reshape([float(i) for i in np.ravel(np.cumsum(data_copy, axis=0))], data_shape)
# scale the data is needed
if scale:
data_copy /= data_stack[levels-1]
data_stack /= data_stack[levels-1]
if heights is not None:
print "WARNING: setting scale and heights does not make sense."
heights = None
elif heights is not None:
data_copy /= data_stack[levels-1]
data_stack /= data_stack[levels-1]
for i in np.arange(num_bars):
data_copy[:,i] *= heights[i]
data_stack[:,i] *= heights[i]
#------------------------------------------------------------------------------
# ticks
if yTicks is not "none":
# it is either a set of ticks or the number of auto ticks to make
real_ticks = True
try:
k = len(yTicks[1])
except:
real_ticks = False
if not real_ticks:
yTicks = float(yTicks)
if scale:
# make the ticks line up to 100 %
y_ticks_at = np.arange(yTicks)/(yTicks-1)
y_tick_labels = np.array(["%0.0f"%(i * 100) for i in y_ticks_at])
else:
# space the ticks along the y axis
y_ticks_at = np.arange(yTicks)/(yTicks-1)*np.max(data_stack)
y_tick_labels = np.array([str(i) for i in y_ticks_at])
yTicks=(y_ticks_at, y_tick_labels)
#------------------------------------------------------------------------------
# plot
if edgeCols is None:
edgeCols = ["none"]*len(cols)
# bars
ax.bar(x,
data_stack[0],
color=cols[0],alpha=0.7,
edgecolor=edgeCols[0],
width=widths,
linewidth=0.5,
align='center'
)
for i in np.arange(1,levels):
ax.bar(x,
data_copy[i],
bottom=data_stack[i-1],
color=cols[i],alpha=0.7,
edgecolor=edgeCols[i],
width=widths,
linewidth=0.5,
align='center'
)
# borders
ax.spines["top"].set_visible(False)
ax.spines["right"].set_visible(False)
ax.spines["bottom"].set_visible(False)
ax.spines["left"].set_visible(False)
# make ticks if necessary
if yTicks is not "none":
ax.tick_params(axis='y', which='both', labelsize=8, direction="out")
ax.yaxis.tick_left()
plt.yticks(yTicks[0], yTicks[1])
else:
plt.yticks([], [])
if xLabels is not None:
ax.tick_params(axis='x', which='both', labelsize=8, direction="out")
ax.xaxis.tick_bottom()
plt.xticks(x, xLabels, rotation='horizontal')
else:
plt.xticks([], [])
# limits
ax.set_xlim(-1.*widths[0]/2., np.sum(widths)-0.5)
ax.set_ylim(0, np.max(data_stack))
# labels
if xlabel != '':
ax.xlabel(xlabel)
if ylabel != '':
ax.ylabel(ylabel)
