Double header in Matplotlib Table
Question:
I need to plot a table in matplotlib. The problem is some columns have one-level headers, some columns have double-level headers.
Here’s what I need:
Here’s simple example for one-level headers:
df = pd.DataFrame()
df['Animal'] = ['Cow', 'Bear']
df['Weight'] = [250, 450]
df['Favorite'] = ['Grass', 'Honey']
df['Least Favorite'] = ['Meat', 'Leaves']
df
fig = plt.figure(figsize=(9,2))
ax=plt.subplot(111)
ax.axis('off')
table = ax.table(cellText=df.values, colColours=['grey']*df.shape[1], bbox=[0, 0, 1, 1], colLabels=df.columns)
plt.savefig('Table.jpg')
Last chunk of code produces next picture:
What changes do I need to make to have table I need?
Answers:
I guess that the only way is to add the headers manually. You can control their exact position and size with the bbox argument. See my example below. You can get more details from this answer: https://stackoverflow.com/a/37440236/2912478
#!/usr/bin/env python
import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame()
df['Animal'] = ['Cow', 'Bear']
df['Weight'] = [250, 450]
df['Favorite'] = ['Grass', 'Honey']
df['Least Favorite'] = ['Meat', 'Leaves']
df
fig = plt.figure(figsize=(9,2))
ax=plt.subplot(111)
ax.axis('off')
plt.table(cellText=[['Animal', 'Weight']],
loc='bottom',
bbox=[0, 0.6, 0.5, 0.3]
)
plt.table(cellText=[['Food']],
loc='bottom',
bbox=[0.5, 0.75, 0.5, 0.15]
)
plt.table(cellText=[['Favorite', 'Least favorite']],
loc='bottom',
bbox=[0.5, 0.6, 0.5, 0.15]
)
plt.table(cellText=df.values,
loc='bottom',
bbox=[0, 0, 1, 0.6]
)
plt.show()
Here is the output I get:
Yet another option would be to utilize matplotlib.gridspec.GridSpec to plot values and columns using a custom layout:
def format_axes(fig):
for i, ax in enumerate(fig.axes):
ax.tick_params(labelbottom=False, labelleft=False, labelright=False)
ax.get_xaxis().set_ticks([])
ax.get_yaxis().set_ticks([])
df = pd.DataFrame()
df['Animal'] = ['Cow', 'Bear']
df['Weight'] = [250, 450]
df['Favorite'] = ['Grass', 'Honey']
df['Least Favorite'] = ['Meat', 'Leaves']
fig = plt.figure(figsize=(9, 2))
gs = GridSpec(3, 4, figure=fig, wspace=0.0, hspace=0.0,height_ratios=[1, 1, 4])
# plot table header
ax1 = fig.add_subplot(gs[:-1, 0])
ax1.text(0.5, 0.5, df.columns[0], va="center", ha="center")
ax2 = fig.add_subplot(gs[:-1, 1])
ax2.text(0.5, 0.5, df.columns[1], va="center", ha="center")
ax3 = fig.add_subplot(gs[0, -2:])
ax3.text(0.5, 0.5, "Food", va="center", ha="center")
ax4 = fig.add_subplot(gs[1, -2])
ax4.text(0.5, 0.5, df.columns[2], va="center", ha="center")
ax5 = fig.add_subplot(gs[1, -1])
ax5.text(0.5, 0.5, df.columns[3], va="center", ha="center")
# plot table data
ax6 = fig.add_subplot(gs[-1, :])
table = ax6.table(cellText=df.values, cellLoc='center', bbox=[0, 0, 1, 1])
format_axes(fig)
plt.show()
Result
Cell merge solution
You can merge the cells produced by ax.table, a la the cell merge function in an Excel spreadsheet. This allows for a completely automated solution in which you don’t need to fiddle with any coordinates (save for the indices of the cell you want to merge):
import matplotlib.pyplot as plt
import pandas as pd
df = pd.DataFrame()
df['Animal'] = ['Cow', 'Bear']
df['Weight'] = [250, 450]
df['Favorite'] = ['Grass', 'Honey']
df['Least Favorite'] = ['Meat', 'Leaves']
fig = plt.figure(figsize=(9,2))
ax=fig.gca()
ax.axis('off')
r,c = df.shape
# ensure consistent background color
ax.table(cellColours=[['lightgray']] + [['none']], bbox=[0,0,1,1])
# plot the real table
table = ax.table(cellText=np.vstack([['', '', 'Food', ''], df.columns, df.values]),
cellColours=[['none']*c]*(2 + r), bbox=[0, 0, 1, 1])
# need to draw here so the text positions are calculated
fig.canvas.draw()
# do the 3 cell merges needed
mergecells(table, (1,0), (0,0))
mergecells(table, (1,1), (0,1))
mergecells(table, (0,2), (0,3))
Output:
Here’s the code for the mergecells function used above:
import matplotlib as mpl
def mergecells(table, ix0, ix1):
ix0,ix1 = np.asarray(ix0), np.asarray(ix1)
d = ix1 - ix0
if not (0 in d and 1 in np.abs(d)):
raise ValueError("ix0 and ix1 should be the indices of adjacent cells. ix0: %s, ix1: %s" % (ix0, ix1))
if d[0]==-1:
edges = ('BRL', 'TRL')
elif d[0]==1:
edges = ('TRL', 'BRL')
elif d[1]==-1:
edges = ('BTR', 'BTL')
else:
edges = ('BTL', 'BTR')
# hide the merged edges
for ix,e in zip((ix0, ix1), edges):
table[ix[0], ix[1]].visible_edges = e
txts = [table[ix[0], ix[1]].get_text() for ix in (ix0, ix1)]
tpos = [np.array(t.get_position()) for t in txts]
# center the text of the 0th cell between the two merged cells
trans = (tpos[1] - tpos[0])/2
if trans[0] > 0 and txts[0].get_ha() == 'right':
# reduce the transform distance in order to center the text
trans[0] /= 2
elif trans[0] < 0 and txts[0].get_ha() == 'right':
# increase the transform distance...
trans[0] *= 2
txts[0].set_transform(mpl.transforms.Affine2D().translate(*trans))
# hide the text in the 1st cell
txts[1].set_visible(False)
In addition to @tel’s answer, I’ve made some changes to his code to solve my own problem – to merge more than 2 cells. Here’s what I got:
def mergecells(table, cells):
'''
Merge N matplotlib.Table cells
Parameters
-----------
table: matplotlib.Table
the table
cells: list[set]
list of sets od the table coordinates
- example: [(0,1), (0,0), (0,2)]
Notes
------
https://stackoverflow.com/a/53819765/12684122
'''
cells_array = [np.asarray(c) for c in cells]
h = np.array([cells_array[i+1][0] - cells_array[i][0] for i in range(len(cells_array) - 1)])
v = np.array([cells_array[i+1][1] - cells_array[i][1] for i in range(len(cells_array) - 1)])
# if it's a horizontal merge, all values for `h` are 0
if not np.any(h):
# sort by horizontal coord
cells = np.array(sorted(list(cells), key=lambda v: v[1]))
edges = ['BTL'] + ['BT' for i in range(len(cells) - 2)] + ['BTR']
elif not np.any(v):
cells = np.array(sorted(list(cells), key=lambda h: h[0]))
edges = ['TRL'] + ['RL' for i in range(len(cells) - 2)] + ['BRL']
else:
raise ValueError("Only horizontal and vertical merges allowed")
for cell, e in zip(cells, edges):
table[cell[0], cell[1]].visible_edges = e
txts = [table[cell[0], cell[1]].get_text() for cell in cells]
tpos = [np.array(t.get_position()) for t in txts]
# transpose the text of the left cell
trans = (tpos[-1] - tpos[0])/2
# didn't had to check for ha because I only want ha='center'
txts[0].set_transform(mpl.transforms.Affine2D().translate(*trans))
for txt in txts[1:]:
txt.set_visible(False)
In addition to @olenscki’s answer, here’s a trick for cells’ background color.
As @user1185790 and @Jorge said, cell.set_facecolor() works incorrectly if one merges cell. You can avoid that by overlapping a background table like below.
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
def mergecells(table, cells):
'''
Merge N matplotlib.Table cells
Parameters
-----------
table: matplotlib.Table
the table
cells: list[set]
list of sets od the table coordinates
- example: [(0,1), (0,0), (0,2)]
Notes
------
https://stackoverflow.com/a/53819765/12684122
'''
cells_array = [np.asarray(c) for c in cells]
h = np.array([cells_array[i+1][0] - cells_array[i][0] for i in range(len(cells_array) - 1)])
v = np.array([cells_array[i+1][1] - cells_array[i][1] for i in range(len(cells_array) - 1)])
# if it's a horizontal merge, all values for `h` are 0
if not np.any(h):
# sort by horizontal coord
cells = np.array(sorted(list(cells), key=lambda v: v[1]))
edges = ['BTL'] + ['BT' for i in range(len(cells) - 2)] + ['BTR']
elif not np.any(v):
cells = np.array(sorted(list(cells), key=lambda h: h[0]))
edges = ['TRL'] + ['RL' for i in range(len(cells) - 2)] + ['BRL']
else:
raise ValueError("Only horizontal and vertical merges allowed")
for cell, e in zip(cells, edges):
table[cell[0], cell[1]].visible_edges = e
txts = [table[cell[0], cell[1]].get_text() for cell in cells]
tpos = [np.array(t.get_position()) for t in txts]
# transpose the text of the left cell
trans = (tpos[-1] - tpos[0])/2
# didn't had to check for ha because I only want ha='center'
txts[0].set_transform(mpl.transforms.Affine2D().translate(*trans))
for txt in txts[1:]:
txt.set_visible(False)
contents = (
("Apple", "Banana", "Strawberry", "Melon"),
("Apple", "Banana", "Strawberry", "Melon"),
("Apple", "Banana", "Strawberry", "Melon")
)
bg_colors = (
("r", "y", "r", "g"),
("r", "y", "r", "g"),
("r", "y", "r", "g")
)
# ///////////////////////////////////////////////////////
# Figure 1: Just merging cells resulting in weired color
fig1 = plt.figure()
ax1 = fig1.add_subplot(111)
ax1.axis("off")
ax1.set_title("Figure 1")
table = ax1.table(cellText=contents, bbox=[0, 0, 1, 1], cellLoc="center", cellColours=bg_colors)
mergecells(table, [(0, 1), (1, 1), (2, 1)])
# ///////////////////////////////////////////////////////
# ///////////////////////////////////////////////////////
# Figure 2: Overlap empty table only for cells color
fig2 = plt.figure()
ax2 = fig2.add_subplot(111)
ax2.axis("off")
ax2.set_title("Figure 2")
# 'table_bg' is a background table without any contents
# Set background color of this as you want
table_bg = ax2.table(bbox=[0, 0, 1, 1], cellColours=bg_colors)
for cell in table_bg._cells.values():
cell.set_edgecolor("none")
# 'table' contatins cell texts
# Sset its color to 'none' then merge
bg_none = (
("none", "none", "none", "none"),
("none", "none", "none", "none"),
("none", "none", "none", "none")
)
table = ax2.table(cellText=contents, bbox=[0, 0, 1, 1], cellLoc="center", cellColours=bg_none)
mergecells(table, [(0, 1), (1, 1), (2, 1)])
# ///////////////////////////////////////////////////////
plt.show()
I need to plot a table in matplotlib. The problem is some columns have one-level headers, some columns have double-level headers.
Here’s what I need:
Here’s simple example for one-level headers:
df = pd.DataFrame()
df['Animal'] = ['Cow', 'Bear']
df['Weight'] = [250, 450]
df['Favorite'] = ['Grass', 'Honey']
df['Least Favorite'] = ['Meat', 'Leaves']
df
fig = plt.figure(figsize=(9,2))
ax=plt.subplot(111)
ax.axis('off')
table = ax.table(cellText=df.values, colColours=['grey']*df.shape[1], bbox=[0, 0, 1, 1], colLabels=df.columns)
plt.savefig('Table.jpg')
Last chunk of code produces next picture:
What changes do I need to make to have table I need?
I guess that the only way is to add the headers manually. You can control their exact position and size with the bbox argument. See my example below. You can get more details from this answer: https://stackoverflow.com/a/37440236/2912478
#!/usr/bin/env python
import pandas as pd
import matplotlib.pyplot as plt
df = pd.DataFrame()
df['Animal'] = ['Cow', 'Bear']
df['Weight'] = [250, 450]
df['Favorite'] = ['Grass', 'Honey']
df['Least Favorite'] = ['Meat', 'Leaves']
df
fig = plt.figure(figsize=(9,2))
ax=plt.subplot(111)
ax.axis('off')
plt.table(cellText=[['Animal', 'Weight']],
loc='bottom',
bbox=[0, 0.6, 0.5, 0.3]
)
plt.table(cellText=[['Food']],
loc='bottom',
bbox=[0.5, 0.75, 0.5, 0.15]
)
plt.table(cellText=[['Favorite', 'Least favorite']],
loc='bottom',
bbox=[0.5, 0.6, 0.5, 0.15]
)
plt.table(cellText=df.values,
loc='bottom',
bbox=[0, 0, 1, 0.6]
)
plt.show()
Here is the output I get:
Yet another option would be to utilize matplotlib.gridspec.GridSpec to plot values and columns using a custom layout:
def format_axes(fig):
for i, ax in enumerate(fig.axes):
ax.tick_params(labelbottom=False, labelleft=False, labelright=False)
ax.get_xaxis().set_ticks([])
ax.get_yaxis().set_ticks([])
df = pd.DataFrame()
df['Animal'] = ['Cow', 'Bear']
df['Weight'] = [250, 450]
df['Favorite'] = ['Grass', 'Honey']
df['Least Favorite'] = ['Meat', 'Leaves']
fig = plt.figure(figsize=(9, 2))
gs = GridSpec(3, 4, figure=fig, wspace=0.0, hspace=0.0,height_ratios=[1, 1, 4])
# plot table header
ax1 = fig.add_subplot(gs[:-1, 0])
ax1.text(0.5, 0.5, df.columns[0], va="center", ha="center")
ax2 = fig.add_subplot(gs[:-1, 1])
ax2.text(0.5, 0.5, df.columns[1], va="center", ha="center")
ax3 = fig.add_subplot(gs[0, -2:])
ax3.text(0.5, 0.5, "Food", va="center", ha="center")
ax4 = fig.add_subplot(gs[1, -2])
ax4.text(0.5, 0.5, df.columns[2], va="center", ha="center")
ax5 = fig.add_subplot(gs[1, -1])
ax5.text(0.5, 0.5, df.columns[3], va="center", ha="center")
# plot table data
ax6 = fig.add_subplot(gs[-1, :])
table = ax6.table(cellText=df.values, cellLoc='center', bbox=[0, 0, 1, 1])
format_axes(fig)
plt.show()
Result
Cell merge solution
You can merge the cells produced by ax.table, a la the cell merge function in an Excel spreadsheet. This allows for a completely automated solution in which you don’t need to fiddle with any coordinates (save for the indices of the cell you want to merge):
import matplotlib.pyplot as plt
import pandas as pd
df = pd.DataFrame()
df['Animal'] = ['Cow', 'Bear']
df['Weight'] = [250, 450]
df['Favorite'] = ['Grass', 'Honey']
df['Least Favorite'] = ['Meat', 'Leaves']
fig = plt.figure(figsize=(9,2))
ax=fig.gca()
ax.axis('off')
r,c = df.shape
# ensure consistent background color
ax.table(cellColours=[['lightgray']] + [['none']], bbox=[0,0,1,1])
# plot the real table
table = ax.table(cellText=np.vstack([['', '', 'Food', ''], df.columns, df.values]),
cellColours=[['none']*c]*(2 + r), bbox=[0, 0, 1, 1])
# need to draw here so the text positions are calculated
fig.canvas.draw()
# do the 3 cell merges needed
mergecells(table, (1,0), (0,0))
mergecells(table, (1,1), (0,1))
mergecells(table, (0,2), (0,3))
Output:
Here’s the code for the mergecells function used above:
import matplotlib as mpl
def mergecells(table, ix0, ix1):
ix0,ix1 = np.asarray(ix0), np.asarray(ix1)
d = ix1 - ix0
if not (0 in d and 1 in np.abs(d)):
raise ValueError("ix0 and ix1 should be the indices of adjacent cells. ix0: %s, ix1: %s" % (ix0, ix1))
if d[0]==-1:
edges = ('BRL', 'TRL')
elif d[0]==1:
edges = ('TRL', 'BRL')
elif d[1]==-1:
edges = ('BTR', 'BTL')
else:
edges = ('BTL', 'BTR')
# hide the merged edges
for ix,e in zip((ix0, ix1), edges):
table[ix[0], ix[1]].visible_edges = e
txts = [table[ix[0], ix[1]].get_text() for ix in (ix0, ix1)]
tpos = [np.array(t.get_position()) for t in txts]
# center the text of the 0th cell between the two merged cells
trans = (tpos[1] - tpos[0])/2
if trans[0] > 0 and txts[0].get_ha() == 'right':
# reduce the transform distance in order to center the text
trans[0] /= 2
elif trans[0] < 0 and txts[0].get_ha() == 'right':
# increase the transform distance...
trans[0] *= 2
txts[0].set_transform(mpl.transforms.Affine2D().translate(*trans))
# hide the text in the 1st cell
txts[1].set_visible(False)
In addition to @tel’s answer, I’ve made some changes to his code to solve my own problem – to merge more than 2 cells. Here’s what I got:
def mergecells(table, cells):
'''
Merge N matplotlib.Table cells
Parameters
-----------
table: matplotlib.Table
the table
cells: list[set]
list of sets od the table coordinates
- example: [(0,1), (0,0), (0,2)]
Notes
------
https://stackoverflow.com/a/53819765/12684122
'''
cells_array = [np.asarray(c) for c in cells]
h = np.array([cells_array[i+1][0] - cells_array[i][0] for i in range(len(cells_array) - 1)])
v = np.array([cells_array[i+1][1] - cells_array[i][1] for i in range(len(cells_array) - 1)])
# if it's a horizontal merge, all values for `h` are 0
if not np.any(h):
# sort by horizontal coord
cells = np.array(sorted(list(cells), key=lambda v: v[1]))
edges = ['BTL'] + ['BT' for i in range(len(cells) - 2)] + ['BTR']
elif not np.any(v):
cells = np.array(sorted(list(cells), key=lambda h: h[0]))
edges = ['TRL'] + ['RL' for i in range(len(cells) - 2)] + ['BRL']
else:
raise ValueError("Only horizontal and vertical merges allowed")
for cell, e in zip(cells, edges):
table[cell[0], cell[1]].visible_edges = e
txts = [table[cell[0], cell[1]].get_text() for cell in cells]
tpos = [np.array(t.get_position()) for t in txts]
# transpose the text of the left cell
trans = (tpos[-1] - tpos[0])/2
# didn't had to check for ha because I only want ha='center'
txts[0].set_transform(mpl.transforms.Affine2D().translate(*trans))
for txt in txts[1:]:
txt.set_visible(False)
In addition to @olenscki’s answer, here’s a trick for cells’ background color.
As @user1185790 and @Jorge said, cell.set_facecolor() works incorrectly if one merges cell. You can avoid that by overlapping a background table like below.
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
def mergecells(table, cells):
'''
Merge N matplotlib.Table cells
Parameters
-----------
table: matplotlib.Table
the table
cells: list[set]
list of sets od the table coordinates
- example: [(0,1), (0,0), (0,2)]
Notes
------
https://stackoverflow.com/a/53819765/12684122
'''
cells_array = [np.asarray(c) for c in cells]
h = np.array([cells_array[i+1][0] - cells_array[i][0] for i in range(len(cells_array) - 1)])
v = np.array([cells_array[i+1][1] - cells_array[i][1] for i in range(len(cells_array) - 1)])
# if it's a horizontal merge, all values for `h` are 0
if not np.any(h):
# sort by horizontal coord
cells = np.array(sorted(list(cells), key=lambda v: v[1]))
edges = ['BTL'] + ['BT' for i in range(len(cells) - 2)] + ['BTR']
elif not np.any(v):
cells = np.array(sorted(list(cells), key=lambda h: h[0]))
edges = ['TRL'] + ['RL' for i in range(len(cells) - 2)] + ['BRL']
else:
raise ValueError("Only horizontal and vertical merges allowed")
for cell, e in zip(cells, edges):
table[cell[0], cell[1]].visible_edges = e
txts = [table[cell[0], cell[1]].get_text() for cell in cells]
tpos = [np.array(t.get_position()) for t in txts]
# transpose the text of the left cell
trans = (tpos[-1] - tpos[0])/2
# didn't had to check for ha because I only want ha='center'
txts[0].set_transform(mpl.transforms.Affine2D().translate(*trans))
for txt in txts[1:]:
txt.set_visible(False)
contents = (
("Apple", "Banana", "Strawberry", "Melon"),
("Apple", "Banana", "Strawberry", "Melon"),
("Apple", "Banana", "Strawberry", "Melon")
)
bg_colors = (
("r", "y", "r", "g"),
("r", "y", "r", "g"),
("r", "y", "r", "g")
)
# ///////////////////////////////////////////////////////
# Figure 1: Just merging cells resulting in weired color
fig1 = plt.figure()
ax1 = fig1.add_subplot(111)
ax1.axis("off")
ax1.set_title("Figure 1")
table = ax1.table(cellText=contents, bbox=[0, 0, 1, 1], cellLoc="center", cellColours=bg_colors)
mergecells(table, [(0, 1), (1, 1), (2, 1)])
# ///////////////////////////////////////////////////////
# ///////////////////////////////////////////////////////
# Figure 2: Overlap empty table only for cells color
fig2 = plt.figure()
ax2 = fig2.add_subplot(111)
ax2.axis("off")
ax2.set_title("Figure 2")
# 'table_bg' is a background table without any contents
# Set background color of this as you want
table_bg = ax2.table(bbox=[0, 0, 1, 1], cellColours=bg_colors)
for cell in table_bg._cells.values():
cell.set_edgecolor("none")
# 'table' contatins cell texts
# Sset its color to 'none' then merge
bg_none = (
("none", "none", "none", "none"),
("none", "none", "none", "none"),
("none", "none", "none", "none")
)
table = ax2.table(cellText=contents, bbox=[0, 0, 1, 1], cellLoc="center", cellColours=bg_none)
mergecells(table, [(0, 1), (1, 1), (2, 1)])
# ///////////////////////////////////////////////////////
plt.show()