CODEWITHSUNDEEP
pythonmatplotlibbar-chartlinechart
matthaeus
matthaeus

Reputation: 877

matplotlib: How to combine multiple bars with lines

I have a very simple grouped-bar chart with 5 groups of 4 bars each. I used the example from the matplotlib documentation, which goes like this:

import numpy as np
import matplotlib.pyplot as plt

ind = np.arange(5)
avg_bar1 = (81191,79318,57965,60557,14793)
avg_bar2 = (26826,26615,31364,31088,55472)
avg_bar3 = (36232,38038,38615,39014,40812)
avg_bar4 = (26115,25879,25887,28326,27988)

fig, ax = plt.subplots()

rects1 = ax.bar(ind, avg_bar1, 0.15, label='bar1')
rects2 = ax.bar(ind + 0.15, avg_bar2, 0.15, label='bar2')
rects3 = ax.bar(ind + 0.30, avg_bar3, 0.15, label='bar2')
rects4 = ax.bar(ind + 0.45, avg_bar4, 0.15, label='bar2')

plt.xlabel('Distributions')
plt.ylabel('ms')
plt.xticks(ind + 0.15, ('50/50', '60/40', '70/30', '80/20', '90/10'))
plt.legend()

plt.tight_layout()
plt.show()

Problem

But some values of bars in the corresponding other groups (e.g. bar1 in group1 and bar1 in group2, etc.) do not differ that much from each other.

What I want

So I want to add lines in order to see the trend of each group more clearly. The lines should go from the top of each bar in one group to the top of the bar in the corresponding other groups.

I couldn't find anything similar on the web.

Is that possible?

Upvotes: 5

Views: 11923

Answers (2)

matthaeus
matthaeus

Reputation: 877

Thank you @arsho for your input. I have made it a little more compact. It fixed also the error on the last group of bars in your code. See comments in code. Hope this helps.

For those like me who are new to matplotlib: we can simple plot a line to the subplot, no matter if it already contains bars.

import numpy as np
import matplotlib.pyplot as plt

# fig, is the whole thing; ax1 is a subplot in the figure, 
# so we reference it to plot bars and lines there
fig, ax1 = plt.subplots()

ind = np.arange(3)
width = 0.15

# per dimension
colors = ['#00ff00', '#0000ff', '#ff00ff']
markers = ['x','o','v']
xticklabels = ['50/50', '60/40', '70/30']

# 
group1 = [12,6,5]
group2 = [6,8,12]
group3 = [2,4,9]

#
all_groups = [ group1, group2, group3 ]

# plot each group of bars; loop-variable bar_values contains values for bars
for i, bar_values in enumerate( all_groups ):

  # compute position for each bar
  bar_position = width*i
  ax1.bar( ind + bar_position, bar_values, width, color=colors[i] )

# plot line for each group of bars; loop-variable y_values contains values for lines
for i, y_values in enumerate( all_groups ):

  # moves the beginning of a line to the middle of the bar
  additional_space = (width*i) + (width/2);
  # x_values contains list indices plus additional space
  x_values = [ x + additional_space for x,_ in enumerate( y_values ) ]

  # simply plot the values in y_values
  ax1.plot( x_values, y_values, marker=markers[i], color=colors[i] )

plt.setp([ax1], xticks=ind + width, xticklabels=xticklabels)

plt.tight_layout()
plt.show()

Upvotes: 0

arshovon
arshovon

Reputation: 13651

I have started to learn Matplotlib and Numpy recently and found your question quite interesting.

So, I spend time to create a combined graph of grouped-bar chart and line chart relevant to that grouped-bar chart.

Result: enter image description here

Code:

import numpy as np
import matplotlib.pyplot as plt

ind = np.arange(5)
avg_bar1 = (81191,79318,57965,60557,14793)
avg_bar2 = (26826,26615,31364,31088,55472)
avg_bar3 = (36232,38038,38615,39014,40812)
avg_bar4 = (26115,25879,25887,28326,27988)

rects1 = plt.bar(ind, avg_bar1, 0.15, color='#ff0000',label='bar1')
rects2 = plt.bar(ind + 0.15, avg_bar2, 0.15, color='#00ff00', label='bar2')
rects3 = plt.bar(ind + 0.30, avg_bar3, 0.15, color='#0000ff', label='bar3')
rects4 = plt.bar(ind + 0.45, avg_bar4, 0.15, color='#000000', label='bar4')

high_point_x = []
high_point_y = []    
for i in range(0,5):
    single_bar_group={rects1[i].get_height():rects1[i].get_x() + rects1[i].get_width()/2.0,
                      rects2[i].get_height():rects2[i].get_x() + rects2[i].get_width()/2.0,
                      rects3[i].get_height():rects3[i].get_x() + rects3[i].get_width()/2.0,
                      rects4[i].get_height():rects4[i].get_x() + rects4[i].get_width()/2.0}

    height_list = list(single_bar_group.keys())
    height_list.sort(reverse=True)
    for single_height in height_list:
        high_point_y.append(single_height)
        high_point_x.append(single_bar_group[single_height])
        break

trend_line = plt.plot(high_point_x,high_point_y,marker='o', color='#5b74a8', label='Trend Line')

plt.xlabel('Distributions')
plt.ylabel('ms')
plt.xticks(ind+0.15, ('50/50', '60/40', '70/30', '80/20', '90/10'))
plt.legend()
plt.show()

Upvotes: 8

Related Questions