在 Matplotlib 中按年份绘制条形图

Question

I am trying to plot this DataFrame which records various amounts of money over a yearly series:

from matplotlib.dates import date2num

jp = pd.DataFrame([1000,2000,2500,3000,3250,3750,4500], index=['2011','2012','2013','2014','2015','2016','2017'])
jp.index = pd.to_datetime(jp.index, format='%Y')
jp.columns = ['Money']

I would simply like to make a bar graph out of this using PyPlot (ie pyplot.bar).

I tried:

plt.figure(figsize=(15,5))

xvals = date2num(jp.index.date)
yvals = jp['Money']
plt.bar(xvals, yvals, color='black')

ax = plt.gca()
ax.xaxis_date()

plt.show()

But the chart turns out like this:

1. Only by increasing the width substantially will I start seeing the bars. I have a feeling that this graph is attributing the data to the first date of the year (2011-01-01 for example), hence the massive space between each 'bar' and the thinness of the bars.
2. How can I plot this properly, knowing that this is a yearly series? Ideally the y-axis would contain only the years. Something tells me that I do not need to use date2num() , since this seems like a very common, ordinary plotting exercise.
3. My guess as to where I'm stuck is not handling the year correctly. As of now I have them as DateTimeIndex, but maybe there are other steps I need to take.

This has puzzled me for 2 days. All solutions I found online seems to use DataFrame.plot , but I would rather learn how to use PyPlot properly. I also intend to add two more sets of bars, and it seems like the most common way to do that is through plt.bar() .

Thanks everyone.

Answer 1

You can either do

jp.plot.bar()

which gives:

or plot against the actual years:

plt.bar(jp.index.year, jp.Money)

which gives: