摘要: 7.词云重叠 # 代码12-1 评论去重的代码 import pandas as pd import re import jieba.posseg as psg import numpy as np # 去重,去除完全重复的数据 reviews = pd.read_csv(r"G:\data\dat 阅读全文
posted @ 2023-05-05 22:50 詮釋 阅读(47) 评论(0) 推荐(0)
摘要: # -*- coding: utf-8 -*- # 代码11-1 import osimport pandas as pd # # 修改工作路径到指定文件夹# os.chdir("./") # # 第一种连接方式from sqlalchemy import create_engine engine 阅读全文
posted @ 2023-04-13 16:36 詮釋 阅读(34) 评论(0) 推荐(0)
摘要: # -*- coding: utf-8 -*-"""Created on Mon Mar 20 15:12:41 2023@author: admin"""import pandas as pdimport matplotlib.pyplot as pltinputfile = 'original_ 阅读全文
posted @ 2023-03-28 09:53 詮釋 阅读(64) 评论(0) 推荐(0)
摘要: import pandas as pdinputfile='GoodsOrder.csv'data = pd.read_csv(inputfile,encoding = 'gbk')# 根据id对“Goods”列合并,并使用“,”将各商品隔开data['Goods'] = data['Goods'] 阅读全文
posted @ 2023-03-21 10:12 詮釋 阅读(29) 评论(0) 推荐(0)
摘要: import matplotlib.pyplot as pltimport pandas as pddatafile = 'air_data.csv'resultfile = 'explore.csv'data = pd.read_csv(datafile,encoding='utf-8')expl 阅读全文
posted @ 2023-03-13 22:57 詮釋 阅读(198) 评论(0) 推荐(0)
摘要: import syssys.path.append('../code') # 设置路径import numpy as npimport pandas as pdfrom GM11 import GM11 # 引入自编的灰色预测函数 inputfile1 = 'new_reg_data.csv' # 阅读全文
posted @ 2023-03-05 17:39 詮釋 阅读(56) 评论(0) 推荐(0)
摘要: 1.用python第三方库绘制sinx函数图像 import matplotlib.pyplot as pltplt.rcParams['font.sans-serif'] = ['SimHei']plt.rcParams['axes.unicode_minus'] = False#plt.plot 阅读全文
posted @ 2023-02-26 21:03 詮釋 阅读(69) 评论(0) 推荐(0)
摘要: #定义一个2行3列全为0的矩阵 tensor1 = tf.zeros([2,3]) print(tensor1)"""运行结果:tf.Tensor([[0. 0. 0.][0. 0. 0.]], shape=(2, 3), dtype=float32)"""#定义一个2行2列全为1的矩阵 ones_ 阅读全文
posted @ 2022-04-24 21:14 詮釋 阅读(78) 评论(0) 推荐(0)
摘要: import mathimport pandas as pdimport numpy as npimport matplotlib.pyplot as pltdata_tr = pd.read_csv('3.3 data_tr.txt') # 训练集样本data_te = pd.read_csv(' 阅读全文
posted @ 2022-03-19 18:05 詮釋 阅读(67) 评论(0) 推荐(0)
摘要: #所求目标函数:min x**2 + 2*y**2 - 2*x*y - 2*y from sympy import * from matplotlib import pyplot as plt plt.rcParams['font.sans-serif']=['SimHei'] #指定默认字体 Si 阅读全文
posted @ 2022-01-02 20:15 詮釋 阅读(459) 评论(0) 推荐(0)