The road of Mathematics-python Data Processing (2)

Insert Column

#-*-Coding:utf-8-*-

"""

Created on Mon Mar 09 11:21:02 2015

@author: [Email protected]

"""

Print U "python data analysis \ n"

Import Pandas as PD

Import NumPy as NP

#构造商品销量数据

MYDF = PD. DataFrame ({u ' product area code ': [1,1,3,2,4,3],u ' Product A ': Np.random.randint (0,1000,size=6), U ' product B ': Np.random.randint (0,1000, size=6), U ' product C ': Np.random.randint (0,1000,size=6)})

allsales=mydf.values[:,1]+mydf.values[:,2]+mydf.values[:,3]

#插入一列

Mydf.insert (0,u ' total sales ', PD. Series (Allsales))

#按2个列名先排序, by followed by a column name, indicating by column name

Mynewdf=mydf.sort_index (axis=0, by=[u ' product area code ', U ' total Sales '],ascending=[true,false])

Print MYNEWDF

Python Data analysis

Total sales Product A merchandise B merchandise C product area code

0 1436 805 858 577 1

1 1370 422 606 763 1

3 397 445 41 354 2

5 851 737 629 219 3

2 815 682 133 679 3

4 749 999 521 224 4

>>>

Here's an example.

#-*-Coding:utf-8-*-

"""

Created on Mon Mar 09 11:21:02 2015

@author: [Email protected]

"""

This blog all content is original, if reproduced please indicate source http://blog.csdn.net/myhaspl/

Print U "python data analysis \ n"

Import Pandas as PD

Import NumPy as NP

#构造商品销量数据

MYDF = PD. DataFrame ({u ' product area code ': [1,1,3,2,4,3],u ' Product A ': Np.random.randint (0,1000,size=6), U ' product B ': Np.random.randint (0,1000, size=6), U ' product C ': Np.random.randint (0,1000,size=6)})

allsales=mydf.values[:,1]+mydf.values[:,2]+mydf.values[:,3]

#插入一列

Mydf.insert (0,u ' total sales ', PD. Series (Allsales))

Print MYDF

#删除列

Mynewdf=mydf.drop ([u ' total Sales '],axis=1)

Print MYNEWDF

#移动列

Myb=mynewdf.pop (U ' product B ')

Mynewdf.insert (2,u ' merchandise B ', MYB)

Print MYNEWDF

The results are as follows:

Python Data analysis

Total sales Product A merchandise B merchandise C product area code

0 964 80 940 23 1

1 1188 373 450 737 1

2 1137 907 642 492 3

3 1001 646 952 47 2

4 899 526 19 876 4

5 1225 342 430 792 3

Item A merchandise b commodity C product Area code

0 80 940) 23 1

1 373 450) 737 1

2 907 642) 492 3

3 646 952) 47 2

4 526 19) 876 4

5 342 430) 792 3

Commodity a commodity C commodity B commodity area code

0 80 23) 940 1

1 373 737) 450 1

2 907 492) 642 3

3 646 47) 952 2

4 526 876) 19 4

5 342 792) 430 3

>>>

The road of Mathematics-python Data Processing (2)