How to make a histogram from a list of strings in Python?

Question

I have a list of strings:

a = [\'a\', \'a\', \'a\', \'a\', \'b\', \'b\', \'c\', \'c\', \'c\', \'d\', \'e\', \'e\', \'e\', \'e\', \'e\']

I w

Answer 1

Check out matplotlib.pyplot.bar. There is also numpy.histogram which is more flexible if you want wider bins.

Answer 2

here's a concise all-pandas approach:

a = ['a', 'a', 'a', 'a', 'b', 'b', 'c', 'c', 'c', 'd', 'e', 'e', 'e', 'e', 'e']
pd.Series(a).value_counts().plot('bar')

Answer 3

Using numpy

Using numpy 1.9 or greater:

import numpy as np
a = ['a', 'a', 'a', 'a', 'b', 'b', 'c', 'c', 'c', 'd', 'e', 'e', 'e', 'e', 'e']
labels, counts = np.unique(a,return_counts=True)

This can be plotted using:

import matplotlib.pyplot as plt 
ticks = range(len(counts))
plt.bar(ticks,counts, align='center')
plt.xticks(ticks, labels)

Answer 4

Simple and effective way to make character histrogram in python

import numpy as np

import matplotlib.pyplot as plt

from collections import Counter



a = []
count =0
d = dict()
filename = raw_input("Enter file name: ")
with open(filename,'r') as f:
    for word in f:
        for letter  in word:
            if letter not in d:
                d[letter] = 1
            else:
                d[letter] +=1
num = Counter(d)
x = list(num.values())
y = list(num.keys())

x_coordinates = np.arange(len(num.keys()))
plt.bar(x_coordinates,x)
plt.xticks(x_coordinates,y)
plt.show()
print x,y

Answer 5

Very easy with Pandas.

import pandas
from collections import Counter
a = ['a', 'a', 'a', 'a', 'b', 'b', 'c', 'c', 'c', 'd', 'e', 'e', 'e', 'e', 'e']
letter_counts = Counter(a)
df = pandas.DataFrame.from_dict(letter_counts, orient='index')
df.plot(kind='bar')

Notice that Counter is making a frequency count, so our plot type is 'bar' not 'hist'.

Answer 6

Rather than use groupby() (which requires your input to be sorted), use collections.Counter(); this doesn't have to create intermediary lists just to count inputs:

from collections import Counter

counts = Counter(a)

You haven't really specified what you consider to be a 'histogram'. Lets assume you wanted to do this on the terminal:

width = 120  # Adjust to desired width
longest_key = max(len(key) for key in counts)
graph_width = width - longest_key - 2
widest = counts.most_common(1)[0][1]
scale = graph_width / float(widest)

for key, size in sorted(counts.items()):
    print('{}: {}'.format(key, int(size * scale) * '*'))

Demo:

>>> from collections import Counter
>>> a = ['a', 'a', 'a', 'a', 'b', 'b', 'c', 'c', 'c', 'd', 'e', 'e', 'e', 'e', 'e']
>>> counts = Counter(a)
>>> width = 120  # Adjust to desired width
>>> longest_key = max(len(key) for key in counts)
>>> graph_width = width - longest_key - 2
>>> widest = counts.most_common(1)[0][1]
>>> scale = graph_width / float(widest)
>>> for key, size in sorted(counts.items()):
...     print('{}: {}'.format(key, int(size * scale) * '*'))
... 
a: *********************************************************************************************
b: **********************************************
c: **********************************************************************
d: ***********************
e: *********************************************************************************************************************

More sophisticated tools are found in the numpy.histogram() and matplotlib.pyplot.hist() functions. These do the tallying for you, with matplotlib.pyplot.hist() also providing you with graph output.