# coding:utf-8 import pandas as pd import numpy as np import matplotlib.pyplot as plt from scipy.interpolate import interp1d data = pd.read_excel('指数.xlsx',header=None,index_col=None) # 数据信息 # print(data.info()) # 查看空值 isnull = data[1].isnull() # print(isnull) # print(data[1]) # 替换空值 data[1] = data[1].fillna('666') # 找出索引 index_ = data[isnull].index.tolist() # print(index_) # 去除空列所在行 data = data.drop(index_) # print(data) x = data[1] y = data[0] # 插值 f1=interp1d(x,y,kind='linear')#线性插值 f2=interp1d(x,y,kind='cubic')#三次样条插值 x_pred=np.arange(1,170,1) y1=f1(x_pred) datas = pd.DataFrame([y1,x_pred]) datas.to_excel('new指数.xlsx') y2=f2(x_pred) plt.figure(figsize=[12,7]) plt.scatter(x,y,s=30,c='red',label='原始指数') plt.plot(x_pred,y1,'b--',label='linear interpolation') # plt.plot(x_pred,y2,'b--',label='cubic') plt.legend(loc='upper left') font_size = {'size':13} plt.ylabel('淘宝指数',font_size) plt.rcParams['font.sans-serif'] = ['SimHei'] # 设置字体为SimHei显示中文 plt.rcParams['axes.unicode_minus'] = False # 设置正常显示符号 plt.show()
