Setting alpha in matplotlib.axes.Axes.table? - matplotlib

Question

I'm trying to understand how I can set the alpha level in a matplotlib table. I tried setting it with a global rcParams, but not quite sure how to do that? (I want to change the transparency in the header color). In general I'm not sure this can be done globally, if not, how do i pass the parameter to table? Thx in advance.
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from cycler import cycler
import six
# Set universal font and transparency
plt.rcParams["font.family"] = "DejaVu Sans"
plt.rcParams['axes.prop_cycle'] = cycler(alpha=[0.5])
raw_data = dict(Simulation=[42, 39, 86, 15, 23, 57],
SP500=[52, 41, 79, 80, 34, 47],
NASDAQ=[62, 37, 84, 51, 67, 32],
Benchmark=[72, 43, 36, 26, 53, 88])
df = pd.DataFrame(raw_data, index=pd.Index(
['Sharpe Ratio', 'Sortino Ratio', 'Calmars Ratio', 'VaR', 'CVaR', 'Max DD'], name='Metric'),
columns=pd.Index(['Simulation', 'SP500', 'NASDAQ', 'Benchmark'], name='Series'))
def create_table(data, col_width=None, row_height=None, font_size=None,
header_color='#000080', row_colors=None, edge_color='w',
header_columns=0, ax=None, bbox=None):
if row_colors is None:
row_colors = ['#D8D8D8', 'w']
if bbox is None:
bbox = [0, 0, 1, 1]
if ax is None:
size = (np.array(data.shape[::-1]) + np.array([0, 1])) * np.array([col_width, row_height])
fig, ax = plt.subplots(figsize=size)
ax.axis('off')
ax.axis([0, 1, data.shape[0], -1])
data_table = ax.table(cellText=data.values, colLabels=data.columns, rowLabels=data.index,
bbox=bbox, cellLoc='center', rowLoc='left', colLoc='center',
colWidths=([col_width] * len(data.columns)))
cell_map = data_table.get_celld()
for i in range(0, len(data.columns)):
cell_map[(0, i)].set_height(row_height * 0.20)
data_table.auto_set_font_size(False)
data_table.set_fontsize(font_size)
for k, cell in six.iteritems(data_table._cells):
cell.set_edgecolor(edge_color)
if k[0] == 0 or k[1] < header_columns:
cell.set_text_props(weight='bold', color='w')
cell.set_facecolor(header_color)
else:
cell.set_facecolor(row_colors[k[0] % len(row_colors)])
return ax
ax = create_table(df, col_width=1.5, row_height=0.5, font_size=8)
ax.set_title("Risk Measures", fontweight='bold')
ax.axis('off')
plt.tight_layout()
plt.savefig('risk_parameter_table[1].pdf')
plt.show()

Answer 1

You can set_alpha() manually on the table's _cells.
If you only want to change the headers, check if row == 0 or col == -1:
def create_table(...):
...
for (row, col), cell in data_table._cells.items():
if (row == 0) or (col == -1):
cell.set_alpha(0.5)
return ax