基于IRIS数据库画出每类在每个特征上的分布直方图(纵轴为样本数量)

from calendar import c

import csv

import matplotlib.pyplot as plt

import numpy as np

import pandas as pd



file = open('iris.csv')

reader=csv.reader(file)

data=list(reader)



x=list()

y=list()

x22=list()

x33=list()

for i in range(1,51):

    x.append(data[i][2])

x1 = list(map(float, x))

for i in range(51,101):

    x22.append(data[i][2])

x2 = list(map(float, x22))

for i in range(101,151):

    x33.append(data[i][2])

x3 = list(map(float, x33))

print(x1)

print(x2)

print(x3)

# 对数据进行切片，将数据按照从最小值到最大值分组，分成20组

#bins = np.linspace(min(x1),max(x1),4)

bins=[2,3,4,5,6,7]

print(min(x1))

print(min(x2))

print(min(x3))

print(max(x1))

print(max(x2))

print(max(x3))

plt.hist([x1,x2,x3],bins,color=['red','blue','green'],label=['setosa','versicolor','virginica'])  

#plt.matplotlib.pyplot.hist(x1,bins,color='red',label='setosa')  

plt.legend()

plt.ylabel('number')

plt.xlabel('Width')

plt.title(u'Sepal.Width')

plt.show()