(NOTE: You can keep up with progress best at github, but can always search on “slopegraph” here or just hit the tag page: “slopegraph” regularly)
I’ve been a bit obsessed with slopegraphs (a.k.a “Tufte table-chart”) of late and very dissatisfied with the lack of tools to make this particular visualization tool more prevalent. While my ultimate goal is to have a user-friendly modern web app or platform app that’s as easy as a “drag & drop” of a CSV file, this first foray will require a bit (not much, really!) of elbow grease to be used.
For those who want to get right to the code, head on over to github and have a look (I’ll post all updates there). Setup, sample & source are also below.
First, you’ll need a modern Python install. I did all the development on Mac OS Mountain Lion (beta) with the stock Python 2.7 build. You’ll also need the Cairo 2D graphics library which built and installed perfectly from source, even on ML, so it should work fine for you. If you want something besides PDF rendering, you may need additional libraries, but PDF is decent for hi-res embedding, converting to jpg/png (see below) and tweaking in programs like Illustrator.
If you search for “Gender Comparisons” in the comments on this post at Tufte’s blog, you’ll see what I was trying to reproduce in this bit of skeleton code (below). By modifying the CSV file you’re using [line 21] and then which fields are relevant [lines 45-47] you should be able to make your own basic slopegraphs without much trouble.
If you catch any glitches, add some tweak or have a slopegraph “wish list”, let me know here, twitter (@hrbrmstr) or over at github.
# slopegraph.py
#
# Author: Bob Rudis (@hrbrmstr)
#
# Basic Python skeleton to do simple two value slopegraphs
# with output to PDF (most useful form for me...Cairo has tons of options)
#
# Find out more about & download Cairo here:
# http://cairographics.org/
#
# 2012-05-28 - 0.5 - Initial github release. Still needs some polish
#
import csv
import cairo
# original data source: http://www.calvin.edu/~stob/data/television.csv
# get a CSV file to work with
slopeReader = csv.reader(open('television.csv', 'rb'), delimiter=',', quotechar='"')
starts = {} # starting "points"/
ends = {} # ending "points"
# Need to refactor label max width into font calculations
# as there's no guarantee the longest (character-wise)
# label is the widest one
startLabelMaxLen = 0
endLabelMaxLen = 0
# build a base pair array for the final plotting
# wastes memory, but simplifies plotting
pairs = []
for row in slopeReader:
# add chosen values (need start/end for each CSV row)
# to the final plotting array. Try this sample with
# row[1] (average life span) instead of row[5] to see some
# of the scaling in action
lab = row[0] # label
beg = row[5] # male life span
end = row[4] # female life span
pairs.append( (float(beg), float(end)) )
# combine labels of common values into one string
# also (as noted previously, inappropriately) find the
# longest one
if beg in starts:
starts[beg] = starts[beg] + "; " + lab
else:
starts[beg] = lab
if ((len(starts[beg]) + len(beg)) > startLabelMaxLen):
startLabelMaxLen = len(starts[beg]) + len(beg)
s1 = starts[beg]
if end in ends:
ends[end] = ends[end] + "; " + lab
else:
ends[end] = lab
if ((len(ends[end]) + len(end)) > endLabelMaxLen):
endLabelMaxLen = len(ends[end]) + len(end)
e1 = ends[end]
# sort all the values (in the event the CSV wasn't) so
# we can determine the smallest increment we need to use
# when stacking the labels and plotting points
startSorted = [(k, starts[k]) for k in sorted(starts)]
endSorted = [(k, ends[k]) for k in sorted(ends)]
startKeys = sorted(starts.keys())
delta = max(startSorted)
for i in range(len(startKeys)):
if (i+1 <= len(startKeys)-1):
currDelta = float(startKeys[i+1]) - float(startKeys[i])
if (currDelta < delta):
delta = currDelta
endKeys = sorted(ends.keys())
for i in range(len(endKeys)):
if (i+1 <= len(endKeys)-1):
currDelta = float(endKeys[i+1]) - float(endKeys[i])
if (currDelta < delta):
delta = currDelta
# we also need to find the absolute min & max values
# so we know how to scale the plots
lowest = min(startKeys)
if (min(endKeys) < lowest) : lowest = min(endKeys)
highest = max(startKeys)
if (max(endKeys) > highest) : highest = max(endKeys)
# just making sure everything's a number
# probably should move some of this to the csv reader section
delta = float(delta)
lowest = float(lowest)
highest = float(highest)
startLabelMaxLen = float(startLabelMaxLen)
endLabelMaxLen = float(endLabelMaxLen)
# setup line width and font-size for the Cairo
# you can change these and the constants should
# scale the plots accordingly
FONT_SIZE = 9
LINE_WIDTH = 0.5
# there has to be a better way to get a base "surface"
# to do font calculations besides this. we're just making
# this Cairo surface to we know the max pixel width
# (font extents) of the labels in order to scale the graph
# accurately (since width/height are based, in part, on it)
filename = 'slopegraph.pdf'
surface = cairo.PDFSurface (filename, 8.5*72, 11*72)
cr = cairo.Context (surface)
cr.save()
cr.select_font_face("Sans", cairo.FONT_SLANT_NORMAL, cairo.FONT_WEIGHT_NORMAL)
cr.set_font_size(FONT_SIZE)
cr.set_line_width(LINE_WIDTH)
xbearing, ybearing, sWidth, sHeight, xadvance, yadvance = (cr.text_extents(s1))
xbearing, ybearing, eWidth, eHeight, xadvance, yadvance = (cr.text_extents(e1))
xbearing, ybearing, spaceWidth, spaceHeight, xadvance, yadvance = (cr.text_extents(" "))
cr.restore()
cr.show_page()
surface.finish()
# setup some more constants for plotting
# all of these are malleable and should cascade nicely
X_MARGIN = 10
Y_MARGIN = 10
SLOPEGRAPH_CANVAS_SIZE = 200
spaceWidth = 5
LINE_HEIGHT = 15
PLOT_LINE_WIDTH = 0.5
width = (X_MARGIN * 2) + sWidth + spaceWidth + SLOPEGRAPH_CANVAS_SIZE + spaceWidth + eWidth
height = (Y_MARGIN * 2) + (((highest - lowest + 1) / delta) * LINE_HEIGHT)
# create the real Cairo surface/canvas
filename = 'slopegraph.pdf'
surface = cairo.PDFSurface (filename, width, height)
cr = cairo.Context (surface)
cr.save()
cr.select_font_face("Sans", cairo.FONT_SLANT_NORMAL, cairo.FONT_WEIGHT_NORMAL)
cr.set_font_size(FONT_SIZE)
cr.set_line_width(LINE_WIDTH)
cr.set_source_rgba (0, 0, 0) # need to make this a constant
# draw start labels at the correct positions
# cheating a bit here as the code doesn't (yet) line up
# the actual data values
for k in sorted(startKeys):
label = starts[k]
xbearing, ybearing, lWidth, lHeight, xadvance, yadvance = (cr.text_extents(label))
val = float(k)
cr.move_to(X_MARGIN + (sWidth - lWidth), Y_MARGIN + (highest - val) * LINE_HEIGHT * (1/delta) + LINE_HEIGHT/2)
cr.show_text(label + " " + k)
cr.stroke()
# draw end labels at the correct positions
# cheating a bit here as the code doesn't (yet) line up
# the actual data values
for k in sorted(endKeys):
label = ends[k]
xbearing, ybearing, lWidth, lHeight, xadvance, yadvance = (cr.text_extents(label))
val = float(k)
cr.move_to(width - X_MARGIN - eWidth - (4*spaceWidth), Y_MARGIN + (highest - val) * LINE_HEIGHT * (1/delta) + LINE_HEIGHT/2)
cr.show_text(k + " " + label)
cr.stroke()
# do the actual plotting
cr.set_line_width(PLOT_LINE_WIDTH)
cr.set_source_rgba (0.75, 0.75, 0.75) # need to make this a constant
for s1,e1 in pairs:
cr.move_to(X_MARGIN + sWidth + spaceWidth + 20, Y_MARGIN + (highest - s1) * LINE_HEIGHT * (1/delta) + LINE_HEIGHT/2)
cr.line_to(width - X_MARGIN - eWidth - spaceWidth - 20, Y_MARGIN + (highest - e1) * LINE_HEIGHT * (1/delta) + LINE_HEIGHT/2)
cr.stroke()
cr.restore()
cr.show_page()
surface.finish()
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