DataFrame 学习笔记

由数组字典构造DataFrame

from pandas import Series,DataFrame
import numpy as np 
import pandas as pd
data={'state':['ohio','ohio','ohio','Nevada','Nevada'],
      'year':[2000,2001,2002,2001,2002],
      'pop':[1.5,1.7,3.6,2.4,2.9]}

frame=DataFrame(data)

Out[103]: 
   pop   state  year
0  1.5    ohio  2000
1  1.7    ohio  2001
2  3.6    ohio  2002
3  2.4  Nevada  2001
4  2.9  Nevada  2002

改变序列顺序

DataFrame(data,columns=['year','state','pop'])

Out[104]: 
   year   state  pop
0  2000    ohio  1.5
1  2001    ohio  1.7
2  2002    ohio  3.6
3  2001  Nevada  2.4
4  2002  Nevada  2.9

改变标签，增加列没有数据，显示NaN

frame2=DataFrame(data,columns=['year','state','pop','debt'], index=['one','two','three','four','five'])

frame2
Out[108]: 
       year   state  pop debt
one    2000    ohio  1.5  NaN
two    2001    ohio  1.7  NaN
three  2002    ohio  3.6  NaN
four   2001  Nevada  2.4  NaN
five   2002  Nevada  2.9  NaN

frame2.columns
Out[111]: Index(['year', 'state', 'pop', 'debt'], dtype='object')

frame2.state=frame2[‘state’] 用法相同

frame2.state
Out[112]: 
one        ohio
two        ohio
three      ohio
four     Nevada
five     Nevada
Name: state, dtype: object

frame2['state']
Out[113]: 
one        ohio
two        ohio
three      ohio
four     Nevada
five     Nevada
Name: state, dtype: object

debt赋值

frame2['debt']=16.5

frame2
Out[115]: 
       year   state  pop  debt
one    2000    ohio  1.5  16.5
two    2001    ohio  1.7  16.5
three  2002    ohio  3.6  16.5
four   2001  Nevada  2.4  16.5
five   2002  Nevada  2.9  16.5

frame2['debt']=np.arange(5)
frame2.debt=np.arange(5)

frame2
Out[120]: 
       year   state  pop  debt
one    2000    ohio  1.5     0
two    2001    ohio  1.7     1
three  2002    ohio  3.6     2
four   2001  Nevada  2.4     3
five   2002  Nevada  2.9     4

val=Series([-1.2,-1.5,-1.7],index=['two','four','five'])

frame2['debt']=val

frame2
Out[127]: 
       year   state  pop  debt
one    2000    ohio  1.5   NaN
two    2001    ohio  1.7  -1.2
three  2002    ohio  3.6   NaN
four   2001  Nevada  2.4  -1.5
five   2002  Nevada  2.9  -1.7

frame2['eastern']=frame2.state=='ohio'

frame2
Out[129]: 
       year   state  pop  debt eastern
one    2000    ohio  1.5   NaN    True
two    2001    ohio  1.7  -1.2    True
three  2002    ohio  3.6   NaN    True
four   2001  Nevada  2.4  -1.5   False
five   2002  Nevada  2.9  -1.7   False

删除列

del frame2['eastern']

frame2
Out[131]: 
       year   state  pop  debt
one    2000    ohio  1.5   NaN
two    2001    ohio  1.7  -1.2
three  2002    ohio  3.6   NaN
four   2001  Nevada  2.4  -1.5
five   2002  Nevada  2.9  -1.7

frame2.columns
Out[132]: Index(['year', 'state', 'pop', 'debt'], dtype='object')