從文本文件中使用數據來構建線性迴歸

Question

Poverty.txt

我使用poverty.txt文件從上述鏈接來構造在python線性迴歸。當我嘗試使用熊貓導入文件時，我在列之間獲得更多空間。因此，我無法獲取所需列的正確結果。我使用下面的代碼

from numpy import arange,array,ones#,random,linalg 
from pylab import plot,show 
from scipy import stats 
import numpy as np 
import pandas as pd 


data = pd.read_csv('poverty.txt',delimiter='\t') 
print "data=",data 

print data[['Location','PovPct']] 

我收到的時候我在打印數據的輸出如下：

Answer 1

import pandas as pd 
data = pd.read_csv("poverty.txt", delim_whitespace=True) 
data 

Out[2]: 
       Location PovPct Brth15to17 Brth18to19 ViolCrime TeenBrth 
0    Alabama 20.1  31.5  88.7  11.2  54.5 
1     Alaska  7.1  18.9  73.7  9.1  39.5 
2    Arizona 16.1  35.0  102.5  10.4  61.2 
3    Arkansas 14.9  31.6  101.7  10.4  59.9 
4    California 16.7  22.6  69.1  11.2  41.1 
5    Colorado  8.8  26.2  79.1  5.8  47.0 
6   Connecticut  9.7  14.1  45.1  4.6  25.8 
7    Delaware 10.3  24.7  77.8  3.5  46.3 
8 District_of_Columbia 22.0  44.8  101.5  65.0  69.1 
9    Florida 16.2  23.2  78.4  7.3  44.5 
10    Georgia 12.1  31.4  92.8  9.5  55.7 
11    Hawaii 10.3  17.7  66.4  4.7  38.2 
12     Idaho 14.5  18.4  69.1  4.1  39.1 
13    Illinois 12.4  23.4  70.5  10.3  42.2 
14    Indiana  9.6  22.6  78.5  8.0  44.6 
15     Iowa 12.2  16.4  55.4  1.8  32.5 
16    Kansas 10.8  21.4  74.2  6.2  43.0 
17    Kentucky 14.7  26.5  84.8  7.2  51.0 
18    Louisiana 19.7  31.7  96.1  17.0  58.1 
19     Maine 11.2  11.9  45.2  2.0  25.4 
20    Maryland 10.1  20.0  59.6  11.8  35.4 
21   Massachusetts 11.0  12.5  39.6  3.6  23.3 
22    Michigan 12.2  18.0  60.8  8.5  34.8 
23    Minnesota  9.2  14.2  47.3  3.9  27.5 
24   Mississippi 23.5  37.6  103.3  12.9  64.7 
25    Missouri  9.4  22.2  76.6  8.8  44.1 
26    Montana 15.3  17.8  63.3  3.0  36.4 
27    Nebraska  9.6  18.3  64.2  2.9  37.0 
28    Nevada 11.1  28.0  96.7  10.7  53.9 
29   New_Hampshire  5.3   8.1  39.0  1.8  20.0 
30   New_Jersey  7.8  14.7  46.1  5.1  26.8 
31   New_Mexico 25.3  37.8  99.5  8.8  62.4 
32    New_York 16.5  15.7  50.1  8.5  29.5 
33  North_Carolina 12.6  28.6  89.3  9.4  52.2 
34   North_Dakota 12.0  11.7  48.7  0.9  27.2 
35     Ohio 11.5  20.1  69.4  5.4  39.5 
36    Oklahoma 17.1  30.1  97.6  12.2  58.0 
37    Oregon 11.2  18.2  64.8  4.1  36.8 
38   Pennsylvania 12.2  17.2  53.7  6.3  31.6 
39   Rhode_Island 10.6  19.6  59.0  3.3  35.6 
40  South_Carolina 19.9  29.2  87.2  7.9  53.0 
41   South_Dakota 14.5  17.3  67.8  1.8  38.0 
42    Tennessee 15.5  28.2  94.2  10.6  54.3 
43     Texas 17.4  38.2  104.3  9.0  64.4 
44     Utah  8.4  17.8  62.4  3.9  36.8 
45    Vermont 10.3  10.4  44.4  2.2  24.2 
46    Virginia 10.2  19.0  66.0  7.6  37.6 
47   Washington 12.5  16.8  57.6  5.1  33.0 
48   West_Virginia 16.7  21.5  80.7  4.9  45.5 
49    Wisconsin  8.5  15.9  57.1  4.3  32.3 
50    Wyoming 12.2  17.7  72.1  2.1  39.9 

和列：

list(data) 
Out[3]: ['Location', 'PovPct', 'Brth15to17', 'Brth18to19', 'ViolCrime', 'TeenBrth']