python - Create Table in subplot

Question

I have a python plot and then would like to have a set of statistics in a table in a subplot adjacent to it. I have used kind of an adhoc approach in which I create a subplot with white axis colors and then make a table in the subplot. You can see that the table has white lines running through it if you look closely. My code is below.

import pandas as pd
import numpy as np
import datetime as dt
import matplotlib.pyplot
from patsy import dmatrices
import statsmodels.api as sm
import matplotlib.gridspec as gridspec
gs = gridspec.GridSpec(1, 2,width_ratios=[6,1])
ax1 = plt.subplot(gs[0])
plt.plot_date(sp_df.index,np.log(sp_df['PX_LAST']),'k')
sells = sp_df[(sp_df['hurst'] > 0.5) & (sp_df['sharpe'] < 0.5) & (sp_df['20dma'] < sp_df['65dma'])].index
buys = sp_df[(sp_df['hurst'] > 0.5) & (sp_df['sharpe'] > 0.5) & (sp_df['20dma'] > sp_df['65dma']) & (sp_df['50dma'] > sp_df['200dma'])].index
plt.plot_date(buys,np.log(sp_df.ix[buys]['PX_LAST']),'g^')
plt.plot_date(sells,np.log(sp_df.ix[sells]['PX_LAST']),'rv')
plt.xlim(sp_df.index[0] - dt.timedelta(days=90),sp_df.index[-1] + dt.timedelta(days=90))
ax2 = plt.subplot(gs[1])
total_return = 2.50
annualized_return = 1.257
sharpe_ratio = .85
max_dd = .12
dd_duration = 300
stats = {"Total Return" : "%0.2f%%" % ((total_return - 1.0) * 100.0),
                 "Annualized Return" : "%0.2f%%" %((annualized_return - 1.0) * 100.0),
                 "Sharpe Ratio" : "%0.2f" % sharpe_ratio,
                 "Max Drawdown" : "%0.2f%%" % (max_dd * 100.0),
                 "Drawdown Duration" : str(dd_duration) + " days"}
bbox=[0.0,0.0,.5, .5]
stats = pd.DataFrame(stats,index=range(1)).T
plt.table(cellText = stats.get_values(),colWidths=[0.6]*2,rowLabels=stats.index,colLabels=['Metrics'],loc='right')
plt.tick_params(axis='both',top='off',left='off',labelleft='off',right='off',bottom='off',labelbottom='off')
ax = plt.gca()
ax.spines['bottom'].set_color('white')
ax.spines['top'].set_color('white')
ax.spines['left'].set_color('white')
ax.spines['right'].set_color('white')
fig = plt.gcf()
fig.set_size_inches(11.5,8.5)

Along with a picture

Answer 1

Based on this answer you can also use Latex to create a table.
For ease of usability, you can create a function that turns your data into the corresponding text-string:

import numpy as np
import matplotlib.pyplot as plt
from math import pi
from matplotlib import rc

rc('text', usetex=True)

# function that creates latex-table
def latex_table(celldata,rowlabel,collabel):
    table = r'egin{table} egin{tabular}{|1|'
    for c in range(0,len(collabel)):
        # add additional columns
        table += r'1|'
    table += r'} hline'

    # provide the column headers
    for c in range(0,len(collabel)-1):
        table += collabel[c]
        table += r'&'
    table += collabel[-1]
    table += r'\ hline'

    # populate the table:
    # this assumes the format to be celldata[index of rows][index of columns]
    for r in range(0,len(rowlabel)):
        table += rowlabel[r]
        table += r'&'
        for c in range(0,len(collabel)-2):
            if not isinstance(celldata[r][c], basestring):
                table += str(celldata[r][c])
            else:
                table += celldata[r][c]
            table += r'&'

        if not isinstance(celldata[r][-1], basestring):
            table += str(celldata[r][-1])
        else:
            table += celldata[r][-1]
        table += r'\ hline'

    table += r'end{tabular} end{table}'

    return table

# set up your data:

celldata = [[32, r'$alpha$', 123],[200, 321, 50]]
rowlabel = [r'1st row', r'2nd row']
collabel = [r' ', r'$alpha$', r'$eta$', r'$gamma$']

table = latex_table(celldata,rowlabel,collabel)

# set up the figure and subplots

fig = plt.figure()

ax1 = fig.add_subplot(121)
ax2 = fig.add_subplot(122)

ax1.plot(np.arange(100))
ax2.text(.1,.5,table, size=50)
ax2.axis('off')

plt.show() 

The underlying idea of this function is to create one long string, called table which can be interpreted as a Latex-command. It is important to import rc and set rc('text', uestec=True) to ensure that the string can be understood as Latex.
The string is appended using +=; the input is as raw string, hence the r. The example data highlights the data format.
Finally, with this example, your figure looks like this: