2. Histogram & Histograms Overlayed

# Create a histogram of any one of the four features

import matplotlib.pyplot as plt

ax = plt.axes()

ax.hist(data.petal_length, bins=25);

ax.set(xlabel='Petal Length (cm)',

       ylabel='Frequency',

       title='Distribution of Petal Lengths');

plt.show()

import matplotlib.pyplot as plt

ax = data.petal_length.plot.hist(bins=20)

ax.set(xlabel='Petal Length (cm)',

       ylabel='Frequency',

       title='Distribution of Petal Lengths');

plt.show()

# Create a single plot with histograms for each feature overlayed

# If Seaborn is not imported

try:

       import seaborn as sns

except:

       print('Seaborn must be installed for this course. Execute the following:')

       print('`conda install seaborn`')

       print('from a terminal and restart the kernel.')

sns.set_context('notebook')

import matplotlib.pyplot as plt

ax = data.plot.hist(bins=25, alpha=0.5)

ax.set_xlabel('Size (cm)');

plt.show()

import matplotlib.pyplot as plt

data.plot(kind="hist", rot=50, bins=25, alpha=0.5)

plt.show()

# To create four separate plots

import matplotlib.pyplot as plt

axList = data.hist(bins=25)

for ax in axList.flatten():

       if ax.is_last_row():

              ax.set_xlabel('Size (cm)')

       if ax.is_first_col():

              ax.set_ylabel('Frequency')

#plt.show()