Example 1: matplotlib histogram
import matplotlib.pyplot as plt
data = [1.7,1.8,2.0,2.2,2.2,2.3,2.4,2.5,2.5,2.5,2.6,2.6,2.8,
2.9,3.0,3.1,3.1,3.2,3.3,3.5,3.6,3.7,4.1,4.1,4.2,4.3]
plt.hist(data, range=(1,4), bins=8)
plt.show()
Example 2: plt normalized histogram
plt.hist(data, density=True)
Example 3: matplotlib histograms
import matplotlib.pyplot as plt
%matplotlib inline
fig, ax = plt.subplots()
ax.hist(x, edgecolor = "black", bins = 5)
ax.set_title("Title")
ax.set_xlabel("X_Label")
ax.set_ylabel("Y_Label")
Example 4: matplotlib histogram python
import pyplot from matplotlib as plt
plt.hist(x_axis_list, y_axis_list)
Example 5: matplotlib histogram
import pyplot from matplotlib as plt
plt.hist(x, bins=None, range=None, density=False, weights=None, cumulative=False, bottom=None, histtype='bar', align='mid', orientation='vertical', rwidth=None, log=False, color=None, label=None, stacked=False, *, data=None, **kwargs)
Example 6: plt.hist using bins
counts, bins = np.histogram(data)
plt.hist(bins[:-1], bins, weights=counts)