histogram

I'm trying to create a histogram of a data column and plot it logarithmically ( y-axis ) and I'm not sure why the following code does not work: import numpy as np import matplotlib.pyplot as plt data = np.loadtxt('foo.bar') fig = plt.figure() ax = fig.add_subplot(111) plt.hist(data, bins=(23.0, 23.5,24.0,24.5,25.0,25.5,26.0,26.5,27.0,27.5,28.0)) ax.set_xlim(23.5, 28) ax.set_ylim(0, 30) ax.grid(True) plt.yscale('log') plt.show() I've also tried instead of plt.yscale('log') adding Log=true in the plt.hist line and also I tried ax.set_yscale('log') , but nothing seems to work. I either get an

I saw on another question that I could use Counter() to count the number of occurrences in a set of strings. So if I have ['A','B','A','C','A','A'] I get Counter({'A':3,'B':1,'C':1}) . But now, how can I use that information to build a histogram for example? For your data it is probably better to use a barchart instead of a histogram. Check out this code: from collections import Counter import numpy as np import matplotlib.pyplot as plt labels, values = zip(*Counter(['A','B','A','C','A','A']).items()) indexes = np.arange(len(labels)) width = 1 plt.bar(indexes, values, width) plt.xticks(indexes

I have a histogram (see below) and I am trying to find the mean and standard deviation along with code which fits a curve to my histogram. I think there is something in SciPy or matplotlib that can help, but every example I've tried doesn't work. import matplotlib.pyplot as plt import numpy as np with open('gau_b_g_s.csv') as f: v = np.loadtxt(f, delimiter= ',', dtype="float", skiprows=1, usecols=None) fig, ax = plt.subplots() plt.hist(v, bins=500, color='#7F38EC', histtype='step') plt.title("Gaussian") plt.axis([-1, 2, 0, 20000]) plt.show() Chris Take a look at this answer for fitting