python数据分析数据标准化及离散化详解

x'=（x-min）/（max-min）

#！／user/bin/env python
#-*- coding:utf-8 -*-
#author:M10
import numpy as np
import pandas as pd
import matplotlib.pylab as plt
import mysql.connector
conn = mysql.connector.connect(host='localhost',
            user='root',
            passwd='123456',
            db='python')#链接本地数据库
sql = 'select price,comment from taob'#sql语句
data = pd.read_sql(sql,conn)#获取数据
#离差标准化
data1 = (data-data.min())/(data.max()-data.min())
print(data1)

x'=（x-平均数）/标准差

#！／user/bin/env python
#-*- coding:utf-8 -*-
#author:M10
import numpy as np
import pandas as pd
import matplotlib.pylab as plt
import mysql.connector
conn = mysql.connector.connect(host='localhost',
            user='root',
            passwd='123456',
            db='python')#链接本地数据库
sql = 'select price,comment from taob'#sql语句
data = pd.read_sql(sql,conn)#获取数据
#标准差标准化
data1 = (data-data.mean())/data.std()
print(data1)

x' = x/10^j

#！／user/bin/env python
#-*- coding:utf-8 -*-
#author:M10
import numpy as np
import pandas as pd
import matplotlib.pylab as plt
import mysql.connector
conn = mysql.connector.connect(host='localhost',
            user='root',
            passwd='123456',
            db='python')#链接本地数据库
sql = 'select price,comment from taob'#sql语句
data = pd.read_sql(sql,conn)#获取数据
#标准差标准化
j = np.ceil(np.log10(data.abs().max()))#进一取整，abs()为取绝对值
data1 = data/10**j
print(data1)

#！／user/bin/env python
#-*- coding:utf-8 -*-
#author:M10
import numpy as np
import pandas as pd
import matplotlib.pylab as plt
import mysql.connector
conn = mysql.connector.connect(host='localhost',
            user='root',
            passwd='123456',
            db='python')#链接本地数据库
sql = 'select price,comment from taob'#sql语句
data = pd.read_sql(sql,conn)#获取数据
#离散化
data1 = data['price'].T.values#获取价格的一维数组
lable=['很低','低','中','高','很高']
data2 = pd.cut(data1,5,labels=lable)
print(data2)