François Dion: Box office plot (the other kind)

Tables can obfuscate understanding

And we have a follow up question on the Pandas read_html wikipedia James Bond article. Namely, how do we quickly visualize the data.

It is true that the table we had in the previous article doesn't help us with easily seeing the trend (it wasn't the purpose). Even trimming this down to just the Bond movie title and box office normalized to 2005 million $ doesn't help us that much, even with the minimum and maximum highlighted:

	Title	Box office.1
1	Dr. No	448.8
2	From Russia with Love	543.8
3	Goldfinger	820.4
4	Thunderball	848.1
5	You Only Live Twice	514.2
6	On Her Majesty's Secret Service	291.5
7	Diamonds Are Forever	442.5
8	Live and Let Die	460.3
9	man with !The Man with the Golden Gun	334.0
10	spy who !The Spy Who Loved Me	533.0
11	Moonraker	535.0
12	For Your Eyes Only	449.4
13	Octopussy	373.8
14	view !A View to a Kill	275.2
15	living !The Living Daylights	313.5
16	Licence to Kill	250.9
17	GoldenEye	518.5
18	Tomorrow Never Dies	463.2
19	world !The World Is Not Enough	439.5
20	Die Another Day	465.4
21	Casino Royale	581.5
22	Quantum of Solace	514.2
23	Skyfall	879.8

Same data, only better

The absolute minimum to get pandas to plot a graph in a Jupyter notebook (I'm assuming you have enabled inline graphics by using %matplotlib inline) is to use the dataframe method plot, ie. df.plot():

The result of df.plot() with no other options

It usually does the right thing, including a readable legend, and picking only the columns that have numbers or dates. We could also have done a bar graph, but in this case would not have been as readable.

Now, let's add a few elements to this. For one thing, I'd like to not only plot a line graph (default) but to add a table directly under the graph. Since we'll have this table under the X axis, let's remove the tick values on X by using xticks=[].

I think we all can agree that a graph should have a title, so we will add that too. And finally, let's make it a bit larger.

ax=df.plot(table=True,xticks=[],title="Bond movies in 2005 dollars (million)",figsize=(17,11))

And how about adding the average value as a dotted horizontal line for the box office?

ax.hlines(y=df.mean()[0],xmin=0,xmax=23,color='b',alpha=0.5,linestyle='dashed',label='Box office average')

Might as well do it for the budget too. So in all we have:

ax = df.plot(table=True, xticks=[], title="Bond movies in 2005 dollars (million)", figsize=(17,11))
ax.hlines(y=df.mean()[0], xmin=0, xmax=23, color='b', alpha=0.5, linestyle='dashed', label='Box office average')
ax.hlines(y=df.mean()[1], xmin=0, xmax=23, color='g', alpha=0.5, linestyle='dashed', label='Budget average')

So, how does it look?

Final result - click to see full size image

The jupyter notebook can be found on github: pandas_bond.ipynb

Francois Dion
@f_dion