I have a Pandas dataframe, and i want to plot it as matplotlib table. So far i have that part working with following code:
import numpy as np
randn = np.random.randn
from pandas import *
idx = Index(arange(1,11))
df = DataFrame(randn(10, 5), index=idx, columns=['A', 'B', 'C', 'D', 'E'])
vals = np.around(df.values,2)
fig = plt.figure(figsize=(15,8))
ax = fig.add_subplot(111, frameon=True, xticks=[], yticks=[])
the_table=plt.table(cellText=vals, rowLabels=df.index, colLabels=df.columns,
colWidths = [0.03]*vals.shape[1], loc='center')
table_props = the_table.properties()
table_cells = table_props['child_artists']
clm = cm.hot(vals)
for cell in table_cells:
cell.set_height(0.04)
# now i would like to set the backgroundcolor of the cell
At the end of this i would like to set the background-color of the cell according to the colormap - but how do i look it up in the clm array without an index?
Another question: can i somehow pass a format string to the table, so that it formats the text to 2 decimal places?
Any hints appreciated, Andy
You can use plt.Normalize()
to normalize your data, and the pass the normalized data to a Colormap
object, for example plt.cm.hot()
.
plt.table()
has an argument cellColours
, which will be used to set the cells' background color accordingly.
Because cm.hot
maps black to the minimal value, I increased the value range when creating the normalization object.
Here is the code:
from matplotlib import pyplot as plt
import numpy as np
randn = np.random.randn
from pandas import *
idx = Index(np.arange(1,11))
df = DataFrame(randn(10, 5), index=idx, columns=['A', 'B', 'C', 'D', 'E'])
vals = np.around(df.values,2)
norm = plt.Normalize(vals.min()-1, vals.max()+1)
colours = plt.cm.hot(normal(vals))
fig = plt.figure(figsize=(15,8))
ax = fig.add_subplot(111, frameon=True, xticks=[], yticks=[])
the_table=plt.table(cellText=vals, rowLabels=df.index, colLabels=df.columns,
colWidths = [0.03]*vals.shape[1], loc='center',
cellColours=colours)
plt.show()
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