plotting 2 dictionaries in matplotlib - matplotlib

Question

I have 2 dictionaries: dict1 = {'Beef':10, 'Poultry': 13, 'Pork': 14, 'Lamb': 11} and dict2 = {'Beef':3, 'Poultry': 1, 'Pork': 17, 'Lamb': 16}
I want to plot a double bar chart using the dictionary keys as the x-axis values, and the associated values on the y-axis. I am using matplotlib for this. does anyone have any information?

Answer 1

This part of the matplotlib documentation may what you are looking for. To plot your data, the x and y values need to be extracted from the dicts, for example via dict.keys() and dict.values().
import matplotlib.pyplot as plt
import numpy as np
dict1 = {'Beef':10, 'Poultry': 13, 'Pork': 14, 'Lamb': 11}
dict2 = {'Beef':3, 'Poultry': 1, 'Pork': 17, 'Lamb': 16}
x = dict1.keys()
y1 = dict1.values()
y2 = dict2.values()
N = len(x)
fig, ax = plt.subplots()
ind = np.arange(N) # the x locations for the groups
width = 0.35 # the width of the bars
p1 = ax.bar(ind, y1, width)
p2 = ax.bar(ind + width, y2, width)
ax.set_xticks(ind + width / 2)
ax.set_xticklabels(x)
ax.legend((p1[0], p2[0]), ('dict1', 'dict2'))
plt.show()
Result:

Answer 2

I'd like to propose a more general approach: instead of just two dicts, what happens if we have a list of dictionaries?
In [89]: from random import randint, seed, shuffle
...: seed(20201213)
...: cats = 'a b c d e f g h i'.split() # categories
...: # List Of Dictionaries
...: lod = [{k:randint(5, 15) for k in shuffle(cats) or cats[:-2]} for _ in range(5)]
...: lod
Out[89]:
[{'d': 14, 'h': 10, 'i': 13, 'f': 13, 'c': 5, 'b': 5, 'a': 14},
{'h': 12, 'd': 5, 'c': 5, 'i': 11, 'b': 14, 'g': 8, 'e': 13},
{'d': 8, 'a': 12, 'f': 7, 'h': 10, 'g': 10, 'c': 11, 'i': 12},
{'g': 11, 'f': 8, 'i': 14, 'h': 11, 'a': 5, 'c': 7, 'b': 8},
{'e': 11, 'h': 13, 'c': 5, 'i': 8, 'd': 12, 'a': 11, 'g': 11}]
As you can see, the keys are not ordered in the same way and the dictionaries do not contain all the possible keys...
Our first step is to find a list of keys (lok), using a set comprehension, followed by sorting the keys (yes, we already know the keys, but here we are looking for a general solution…)
In [90]: lok = sorted(set(k for d in lod for k in d))
The number of elements in the two lists are
In [91]: nk, nd = len(lok), len(lod)
At this point we can compute the width of a single bar, saying that the bar groups are 1 unit apart (hence x = range(nk)) and that we leave 1/3 unit between the groups, we have
In [92]: x, w = range(nk), 0.67/nd
We are ready to go with the plot
In [93]: import matplotlib.pyplot as plt
...: for n, d in enumerate(lod):
...: plt.bar([ξ+n*w for ξ in x], [d.get(k, 0) for k in lok], w,
...: label='dict %d'%(n+1))
...: plt.xticks([ξ+w*nd/2 for ξ in x], lok)
...: plt.legend();
Let's write a small function
def plot_lod(lod, ws=0.33, ax=None, legend=True):
"""bar plot from the values in a list of dictionaries.
lod: list of dictionaries,
ws: optional, white space between groups of bars as a fraction of unity,
ax: optional, the Axes object to draw into,
legend: are we going to draw a legend?
Return: the Axes used to plot and a list of BarContainer objects."""
from matplotlib.pyplot import subplot
from numpy import arange, nan
if ax is None : ax = subplot()
lok = sorted({k for d in lod for k in d})
nk, nd = len(lok), len(lod)
x, w = arange(nk), (1.0-ws)/nd
lobars = [
ax.bar(x+n*w, [d.get(k, nan) for k in lok], w, label='%02d'%(n+1))
for n, d in enumerate(lod)
]
ax.set_xticks(x+w*nd/2-w/2)
ax.set_xticklabels(lok)
if legend : ax.legend()
return ax, lobars
Using the data of the previous example, we get a slightly different graph…