image_output_1.png
from subprocess import check_output

import matplotlib.pyplot as plt

import numpy as np # linear algebra

import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from subprocess import check_output
data = pd.read_csv('../input/Health_AnimalBites.csv')
colorData = data.color.value_counts()

proc_data = data[data.color == 'BLACK'].BreedIDDesc.value_counts()
dogSpecies = list(proc_data.keys())
corrCount = list(proc_data[proc_data.keys()])
dogSpecies = dogSpecies[0:5]
corrCount = corrCount[0:5]
y_pos = np.arange(len(dogSpecies))
plt.xticks(y_pos, dogSpecies)

proc_data = data[data.color == 'BROWN'].BreedIDDesc.value_counts()
dogSpecies = list(proc_data.keys())
corrCount = list(proc_data[proc_data.keys()])
dogSpecies = dogSpecies[0:5]
corrCount = corrCount[0:5]
y_pos = np.arange(len(dogSpecies))
plt.bar(y_pos, corrCount)
plt.xticks(y_pos, dogSpecies)
plt.show()