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Given three set of data with categorical integer x-axis with the same range (0-10):

from itertools import chain
from collections import Counter, defaultdict

from IPython.display import Image
import pandas as pd
import numpy as np

import seaborn as sns
import colorlover as cl
import matplotlib.pyplot as plt

data1 = Counter({8: 10576, 9: 10114, 7: 9504, 6: 7331, 10: 6845, 5: 5007, 4: 3037, 3: 1792, 2: 908, 1: 368, 0: 158})
data2 = Counter({5: 9030, 6: 8347, 4: 8149, 7: 6822, 3: 6153, 8: 5075, 2: 3973, 9: 3205, 1: 2247, 10: 1580, 0: 1059})
data3 = Counter({4: 9884, 5: 9058, 3: 9048, 2: 6942, 6: 6630, 1: 4596, 7: 3784, 0: 2524, 8: 1912, 9: 917, 10: 345})

df_data1 = pd.DataFrame(list(chain(*[(int(k),)*v for k,v in data1.items()])))
df_data2 = pd.DataFrame(list(chain(*[(int(k),)*v for k,v in data2.items()])))
df_data3 = pd.DataFrame(list(chain(*[(int(k),)*v for k,v in data3.items()])))

I can plot three different barcharts for each set of data as such:

sns.set(style="white")
g = sns.factorplot(x=0, data=df_data1, kind="count", color='#4882D5', size=6, aspect=1.5, order=None)
g.set_xticklabels(step=1)
plt.show()
g = sns.factorplot(x=0, data=df_data2, kind="count", color='#9CD2D5', size=6, aspect=1.5, order=None)
g.set_xticklabels(step=1)
plt.show()
g = sns.factorplot(x=0, data=df_data3, kind="count", color='#EF988D', size=6, aspect=1.5, order=None)
g.set_xticklabels(step=1)
plt.show()

[out]:

enter image description here enter image description here enter image description here

What I want to highlight is the fact that:

  • for data1, we see that the center of mass is inclined to the right where the x-axis is higher at 8
  • for data2, it's normally shaped where the center is at 5
  • for data3, the center of mass is at 4 on the lower side.

Imagine:

  • data1 x-axis represents the no. of blueberry a person buys at the supermarket
  • data2 x-axis represents the no. of watermelon a person buys at the supermarket
  • data3 x-axis represents the no. of oranges a person buys at the supermarket

And

  • The y-axis for all 3 datasets represent the number of people who buys the respective no. of fruits as per the dataset.

It's a little hard to convey the message with the barcharts.

Is there a better way to represent the dataset and highlight what I want to say?

Is there a way to present the 3 graphs as one? How would it look like?

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You shoud put the barcharts next to each other as described in this example.

import numpy as np
import matplotlib.pyplot as plt

N = 5
men_means = (20, 35, 30, 35, 27)
men_std = (2, 3, 4, 1, 2)

ind = np.arange(N)  # the x locations for the groups
width = 0.35       # the width of the bars

fig, ax = plt.subplots()
rects1 = ax.bar(ind, men_means, width, color='r', yerr=men_std)

women_means = (25, 32, 34, 20, 25)
women_std = (3, 5, 2, 3, 3)
rects2 = ax.bar(ind + width, women_means, width, color='y', yerr=women_std)

# add some text for labels, title and axes ticks
ax.set_ylabel('Scores')
ax.set_title('Scores by group and gender')
ax.set_xticks(ind + width / 2)
ax.set_xticklabels(('G1', 'G2', 'G3', 'G4', 'G5'))

ax.legend((rects1[0], rects2[0]), ('Men', 'Women'))


def autolabel(rects):
    """
    Attach a text label above each bar displaying its height
    """
    for rect in rects:
        height = rect.get_height()
        ax.text(rect.get_x() + rect.get_width()/2., 1.05*height,
                '%d' % int(height),
                ha='center', va='bottom')

autolabel(rects1)
autolabel(rects2)

plt.show()

enter image description here

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