I am reading a file and calculating the frequency of the top 100 words. I am able to find that and create the following list:

[('test', 510), ('Hey', 362), ("please", 753), ('take', 446), ('herbert', 325), ('live', 222), ('hate', 210), ('white', 191), ('simple', 175), ('harry', 172), ('woman', 170), ('basil', 153), ('things', 129), ('think', 126), ('bye', 124), ('thing', 120), ('love', 107), ('quite', 107), ('face', 107), ('eyes', 107), ('time', 106), ('himself', 105), ('want', 105), ('good', 105), ('really', 103), ('away',100), ('did', 100), ('people', 99), ('came', 97), ('say', 97), ('cried', 95), ('looked', 94), ('tell', 92), ('look', 91), ('world', 89), ('work', 89), ('project', 88), ('room', 88), ('going', 87), ('answered', 87), ('mr', 87), ('little', 87), ('yes', 84), ('silly', 82), ('thought', 82), ('shall', 81), ('circle', 80), ('hallward', 80), ('told', 77), ('feel', 76), ('great', 74), ('art', 74), ('dear',73), ('picture', 73), ('men', 72), ('long', 71), ('young', 70), ('lady', 69), ('let', 66), ('minute', 66), ('women', 66), ('soul', 65), ('door', 64), ('hand',63), ('went', 63), ('make', 63), ('night', 62), ('asked', 61), ('old', 61), ('passed', 60), ('afraid', 60), ('night', 59), ('looking', 58), ('wonderful', 58), ('gutenberg-tm', 56), ('beauty', 55), ('sir', 55), ('table', 55), ('turned', 54), ('lips', 54), ("one's", 54), ('better', 54), ('got', 54), ('vane', 54), ('right',53), ('left', 53), ('course', 52), ('hands', 52), ('portrait', 52), ('head', 51), ("can't", 49), ('true', 49), ('house', 49), ('believe', 49), ('black', 49), ('horrible', 48), ('oh', 48), ('knew', 47), ('curious', 47), ('myself', 47)]

After getting this list, I want to draw histogram using matplotlib. I am trying something as below, but I am not able to draw a proper histogram.

My question: How do I pass the total frequency to the graph? All of my bars are at the same height right now. And even the bin center is not correct. How should I pass data to the ax.hist method on below code? I am trying to update the example from http://matplotlib.org/1.2.1/examples/api/histogram_demo.html.

totalWords = counts.most_common(100)
print(totalWords)
for z in range(len(totalWords)):words.append(totalWords[z][0])x = np.arange(len(words))
#print x
i, s = 100, 15fig = plt.figure()
ax = fig.add_subplot(111)n, bins, patches = ax.hist(x, 50, normed=1, facecolor='green', alpha=0.75)bincenters = 0.5*(bins[1:]+bins[:-1])y = mlab.normpdf(bincenters*1.00, i, s)
l = ax.plot(bincenters, y, 'r--', linewidth=1)ax.set_xlabel('Words')
ax.set_ylabel('Frequency')
ax.set_xlim(50, 160)
ax.set_ylim(0, 0.04)
ax.grid(True)plt.show()

It's a little unclear exactly what you want to graph, and how relevant the matplotlib demo you are adapting actually is.

I'll run through some options, and try and answer your specific questions in each case:

• Using the matplotlib demo, you only need to give ax.hist the list of word frequencies x = words[n][1] ,but this just gives you the relative frequency of the different frequencies... so most of the words occur <100 times, while a couple of words occur much more frequently. This is why your code above returns a histogram of equal bars, because you are giving ax.hist the numbers from 0 to 99 once each. Note that this approach doesn't show the individual words

• Otherwise, I think you want a bar chart with each bar labelled as a different word.

This worked for me.

words = [('test', 510), ('Hey', 362), ("please", 753), ('take', 446),     ('herbert', 325), ('live', 222), ('hate', 210), ('white', 191), ('simple', 175),     ('harry', 172), ('woman', 170), ('basil', 153), ('things', 129), ('think', 126), ('bye', 124), ('thing', 120), ('love', 107), ('quite', 107), ('face', 107), ('eyes', 107), ('time', 106), ('himself', 105), ('want', 105), ('good', 105), ('really', 103), ('away',100), ('did', 100), ('people', 99), ('came', 97), ('say', 97), ('cried', 95), ('looked', 94), ('tell', 92), ('look', 91), ('world', 89), ('work', 89), ('project', 88), ('room', 88), ('going', 87), ('answered', 87), ('mr', 87), ('little', 87), ('yes', 84), ('silly', 82), ('thought', 82), ('shall', 81), ('circle', 80), ('hallward', 80), ('told', 77), ('feel', 76), ('great', 74), ('art', 74), ('dear',73), ('picture', 73), ('men', 72), ('long', 71), ('young', 70), ('lady', 69), ('let', 66), ('minute', 66), ('women', 66), ('soul', 65), ('door', 64), ('hand',63), ('went', 63), ('make', 63), ('night', 62), ('asked', 61), ('old', 61), ('passed', 60), ('afraid', 60), ('night', 59), ('looking', 58), ('wonderful', 58), ('gutenberg-tm', 56), ('beauty', 55), ('sir', 55), ('table', 55), ('turned', 54), ('lips', 54), ("one's", 54), ('better', 54), ('got', 54), ('vane', 54), ('right',53), ('left', 53), ('course', 52), ('hands', 52), ('portrait', 52), ('head', 51), ("can't", 49), ('true', 49), ('house', 49), ('believe', 49), ('black', 49), ('horrible', 48), ('oh', 48), ('knew', 47), ('curious', 47), ('myself', 47)]
wordsdict = {}
for w in words:wordsdict[w[0]]=w[1]plt.bar(range(len(wordsdict)), wordsdict.values(), align='center')
plt.xticks(range(len(wordsdict)), wordsdict.keys())plt.show()