Python: Bar chart from JSON

This page shows how to use Python to read in the data names with counts from JSON text files and make a simple bar chart.

Here are links to the topic series of representing and processing data.

R examples:

Python examples:

Python: Bar chart from text and CSV
Python: Bar chart from JSON (this page)
Python: Bar chart from XML
Python: Bar chart from CSV using Pandas
Python: Bar chart from JSON using Pandas

JavaScript and D3 examples:

JavaScript: SVG bar chart using D3

Julia examples:

Julia: Bar chart from JSON data using StatsPlots

... more to be added ...

The Python json library is used.

import json

Here is one possible JSON way to represent data as a list of lists.

[ ["a",59900], ["b",11302], ["c",14311], ["d",34483], ["e",95247], ["f",17852], ["g",13528], ["h",62509], ["i",46347], ["j",2321], ["k",4449], ["l",25939], ["m",19154], ["n",51311], ["o",54741], ["p",9918], ["q",183], ["r",37468], ["s",44630], ["t",72396], ["u",20651], ["v",7458], ["w",18376], ["x",376], ["y",14814], ["z",234] ]

Here is the Python code to read the above JSON data file and output the results.

Here is the Python code [#2]

import matplotlib.pyplot as plt
import numpy as np
np.random.seed(0)
import json
# Read JSON as list of dicts
jsonFs2 = "./letters1.json"
print("JSON: list of dicts from \"{0:s}\"".format(jsonFs2))
jsonF2 = open(jsonFs2,"r")
jsonList2 = json.load(jsonF2)
jsonF2.close()
# Echo and transform the JSON data
dataList1 = []
print("")
print("\tLetter : Count")
print("")
for name1,count1 in jsonList2:
	dataList1.append([name1,count1])
	print("\t{0:s} : {1:,}".format(name1,count1))
# transform data into needed form
xData1 = []
yData1 = []
for name1,count1 in dataList1:
	xData1.append(name1)
	yData1.append(count1)
# set plot parameters
fontDict1 = {
	"family" : "Verdana",
	"weight" : "bold",
	"size" : 16
	}
plt.rc("font", **fontDict1)
# make the bar chart
rlen1 = 1
clen1 = 1
width1 = 1024
height1 = 360
dpi1 = 72
figsize1 = (width1/dpi1,height1/dpi1)
fig1,ax1 = plt.subplots(rlen1,clen1,figsize=figsize1,dpi=dpi1)
y_pos1 = np.arange(len(xData1))
plt.bar(y_pos1, yData1)
plt.xticks(y_pos1, xData1)
plt.ylabel("Count")
plt.xlabel("Letter")
plt.title("Count by Letter")
# save the bar chart
print("")
pngFs1 = "./count14-2-01.png"
print("{0:s} (chart as image)".format(pngFs1))
fig1.savefig(pngFs1,bbox_inches="tight")

Here is the output of the Python code.

JSON: list of dicts from "./letters1.json"
	Letter : Count
	a : 59,900
	b : 11,302
	c : 14,311
	d : 34,483
	e : 95,247
	f : 17,852
	g : 13,528
	h : 62,509
	i : 46,347
	j : 2,321
	k : 4,449
	l : 25,939
	m : 19,154
	n : 51,311
	o : 54,741
	p : 9,918
	q : 183
	r : 37,468
	s : 44,630
	t : 72,396
	u : 20,651
	v : 7,458
	w : 18,376
	x : 376
	y : 14,814
	z : 234
./count14-2-01.png (chart as image)

This is a simple bar chart for the present purposes. Future topics will cover how to make it look nicer.

Here is one possible JSON way to represent data as a list of dicts, each with a name-value pair.

[ {"name":"a", "value":59900}, {"name":"b", "value":11302}, {"name":"c", "value":14311}, {"name":"d", "value":34483}, {"name":"e", "value":95247}, {"name":"f", "value":17852}, {"name":"g", "value":13528}, {"name":"h", "value":62509}, {"name":"i", "value":46347}, {"name":"j", "value":2321}, {"name":"k", "value":4449}, {"name":"l", "value":25939}, {"name":"m", "value":19154}, {"name":"n", "value":51311}, {"name":"o", "value":54741}, {"name":"p", "value":9918}, {"name":"q", "value":183}, {"name":"r", "value":37468}, {"name":"s", "value":44630}, {"name":"t", "value":72396}, {"name":"u", "value":20651}, {"name":"v", "value":7458}, {"name":"w", "value":18376}, {"name":"x", "value":376}, {"name":"y", "value":14814}, {"name":"z", "value":234} ]

Here is the Python code to read the above JSON data file and output the results. Here is the Python code [#3]

import matplotlib.pyplot as plt
import numpy as np
np.random.seed(0)
import json
# Read JSON as list of dicts
jsonFs2 = "./letters2.json"
print("JSON: list of dicts from \"{0:s}\"".format(jsonFs2))
jsonF2 = open(jsonFs2,"r")
jsonList2 = json.load(jsonF2)
jsonF2.close()
# Echo and transform the JSON data
print("")
print("\tLetter : Count")
print("")
dataList1 = []
for dict1 in jsonList2:
	name1 = dict1["name"]
	count1 = dict1["value"]
	dataList1.append([name1,count1])
	print("\t{0:s} : {1:,}".format(name1,count1))
# transform data into needed form
xData1 = []
yData1 = []
for name1,count1 in dataList1:
	xData1.append(name1)
	yData1.append(count1)
# set plot parameters
fontDict1 = {
	"family" : "Verdana",
	"weight" : "bold",
	"size" : 16
	}
plt.rc("font", **fontDict1)
# make the bar chart
rlen1 = 1
clen1 = 1
width1 = 1024
height1 = 360
dpi1 = 72
figsize1 = (width1/dpi1,height1/dpi1)
fig1,ax1 = plt.subplots(rlen1,clen1,figsize=figsize1,dpi=dpi1)
y_pos1 = np.arange(len(xData1))
plt.bar(y_pos1, yData1)
plt.xticks(y_pos1, xData1)
plt.ylabel("Count")
plt.xlabel("Letter")
plt.title("Count by Letter")
# save the bar chart
print("")
pngFs1 = "./count14-3-01.png"
print("{0:s} (chart as image)".format(pngFs1))
fig1.savefig(pngFs1,bbox_inches="tight")

Here is the output of the Python code.

JSON: list of dicts from "./letters2.json"
	Letter : Count
	a : 59,900
	b : 11,302
	c : 14,311
	d : 34,483
	e : 95,247
	f : 17,852
	g : 13,528
	h : 62,509
	i : 46,347
	j : 2,321
	k : 4,449
	l : 25,939
	m : 19,154
	n : 51,311
	o : 54,741
	p : 9,918
	q : 183
	r : 37,468
	s : 44,630
	t : 72,396
	u : 20,651
	v : 7,458
	w : 18,376
	x : 376
	y : 14,814
	z : 234
./count14-3-01.png (chart as image)

This is a simple bar chart for the present purposes. Future topics will cover how to make it look nicer.