How to plot multiple features with the same tag number in histogram plot

Question

I have a text file including 8 features and 1 class. The data of my file is (data.txt):

1,1,3,2,1,1,1,3,HIGH
1,1,3,1,2,1,1,3,HIGH
1,1,1,1,3,3,1,2,HIGH
1,3,2,1,3,3,3,3,HIGH
1,3,1,2,3,1,2,1,HIGH
2,3,1,2,1,2,2,1,HIGH
2,2,2,2,2,1,2,3,HIGH
2,2,1,1,1,2,2,3,HIGH
3,2,1,3,1,3,3,3,HIGH
3,2,1,2,2,3,3,2,HIGH

In the above file, the first 8 columns are the features. They are tagged with a number that could be 1 or 2 or 3. The last column is the class name (HIGH). Now I want to plot these features based on the tag numbers. I can do it for 3 first column by this code:

import pandas as pd
from matplotlib import pyplot as plt

df = pd.read_csv('data.txt', header=None)

# Features are : A,B,C,...,H
df.columns = ['A', 'B','C', 'D', 'E', 'F', 'G', 'H', 'class']

X = df.ix[:, 0:8].values
y = df.ix[:, 8].values

kind = ['barstacked']
deg = ['HIGH']
pos = ['left','right','mid']
col = ['r','b','y']

with plt.style.context('seaborn-whitegrid'):
    plt.figure(figsize=(8, 6))

    for j in range(0,3):
        for i in range(1):
                plt.hist(X[y == deg[i], j],
                     label=deg[i],
                     bins=30,
                     alpha=0.6, histtype=kind[i], align=pos[j], color=col[j])

    plt.tick_params(axis='both', which='major', labelsize=17)
    plt.xlim(0.75, 3.25)
    plt.tight_layout()
    plt.savefig("figure.png" , format='png', dpi=700)
    plt.show()

Here is the result:

However I could not plot the other 5 columns because I did not know how to put them next to each other as there are only 3 align options (left, mid and right). What I am looking at is a histogram plot for all 8 features that separates the features based on the tag number. A graph like this:

Answer 1

You don't need a histogram here and you can easily generate the required figure using a bar chart because you are just plotting a single frequency here. The idea is as follows:

• Use Counter module from collections to get the frequency of 1, 2, and 3.
• The x-positions for your bar chart will be centered around 1, 2 and 3. However, to have the desired effect, you can tweak the x-positions by offsetting them: first 4 bars to the left of 1, 2, 3 and the next 4 bars to the right of 1, 2, 3. This can be done using an offset parameter (j-4)*0.1 which you add to the x-values. Here 0.1 serves as a nice choice of bar width.
• You don't need an additional loop over i here since it is always 0
• df.ix is deprecated in the newer pandas versions. You will have to use df.iloc instead.

---

Following is how you can do it.

df.columns = ['A', 'B','C', 'D', 'E', 'F', 'G', 'H', 'class']

X = df.ix[:, 0:8].values
y = df.ix[:, 8].values

with plt.style.context('seaborn-whitegrid'):
    plt.figure(figsize=(8, 6))
    for j in range(0,8):
            freqs = Counter(X[y == deg[0], j])
            xvalues = np.array(list(freqs.keys()))
            plt.bar(xvalues+(j-4)*0.1, freqs.values(), width=0.1, 
                    alpha=0.9, edgecolor='k', lw=2)
    plt.tick_params(axis='both', which='major', labelsize=17)
    plt.xlim(0.25, 3.75)
    plt.xticks([1,2,3])
    plt.tight_layout()
    plt.show()