from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
from scipy.optimize import curve_fit
from sklearn.decomposition import PCA
from sklearn.preprocessing import StandardScaler
data = pd.read_csv('D:/xxx/data/hueData.csv', header=None)
#print(data)
# get the rgb value
hue = data.loc[1:,0:0].values
hue = list(map(int, hue))
cd = data.loc[1:,1:1].values
cd = list(map(int, cd))
hueHist = plt.subplot(121)
num_bins = 360
hueHist.hist(hue, num_bins, facecolor='red')
hueHist.set_title('hue frequency',fontsize=12,color='r')
cdHist = plt.subplot(122)
num_bins = 360
cdHist.hist(cd, num_bins, facecolor='b')
cdHist.set_title('cd frequency',fontsize=12,color='b')
plt.show()
