Function to read data from textbook files

# Written by Nishant Malik for course Math 50 Fall 2015 (Dartmouth College) 

def read_tb_data(ch,pr):
    import urllib2
    import numpy as np
    str1='https://netfiles.umn.edu/users/nacht001/www/nachtsheim/Kutner/Chapter%20%20'   
    # chapter number 
    if(ch<10): 
        ch_str=str(ch).zfill(2)
    else:
        ch_str=str(ch)
    if(pr<10):
        pr_str=str(pr).zfill(2)
    else:
        pr_str=str(pr)
    
    str2=str(ch)+'%20Data%20Sets/CH'+ch_str+'PR'+pr_str+'.txt'
    str3=str1+str2
    try: urllib2.urlopen(str3)
    except urllib2.URLError as e:
        print(e.reason), '\nChapter number or problem number is wrong. Try again!'
        return np.array([])
    flink = urllib2.urlopen(str3)
    data=[]
    for line in flink: 
        lines=line.strip('\r\n'); lines=lines.split();
        data.append(lines) 
    flink.close()    
    colnos=len(data[0])
    j=0; xdata = np.zeros((len(data),colnos))
    for line in data:
        for k in range(0,colnos):
            xdata[j,k]=data[j][k]
        j=j+1
    return xdata 
 

This function can also be saved in a separte file in your working directory, with a file name. For example lets save it as read_data_fx. It can be imported as shown below.

# import the above described function if saved in file named  "read_data_fx"
from read_data_fx import read_tb_data

A wrong chapter number or problem number will raise a error (exception). For example:

#There is no data for problem 10 in chapeter 2 
data=read_tb_data(2,10)

Not Found 
Chapter number or problem number is wrong. Try again!

# There is data for problem 20 in chapter 1
data=read_tb_data(1,20)

# we can see what is inside data as follows 
#no. of rows and columns in the data 
rown,coln=data.shape
print 'numbers of columns =',coln, 'numbers of rows=', rown 
print 'First column of the data =',  data[:,0]
print 'Second column of the data =',  data[:,1]

numbers of columns = 2 numbers of rows= 45
First column of the data = [  20.   60.   46.   41.   12.  137.   68.   89.    4.   32.  144.  156.
   93.   36.   72.  100.  105.  131.  127.   57.   66.  101.  109.   74.
  134.  112.   18.   73.  111.   96.  123.   90.   20.   28.    3.   57.
   86.  132.  112.   27.  131.   34.   27.   61.   77.]
Second column of the data = [  2.   4.   3.   2.   1.  10.   5.   5.   1.   2.   9.  10.   6.   3.   4.
   8.   7.   8.  10.   4.   5.   7.   7.   5.   9.   7.   2.   5.   7.   6.
   8.   5.   2.   2.   1.   4.   5.   9.   7.   1.   9.   2.   2.   4.   5.]

Function to read tables from examples in the textbook

def read_tb_dataTA(ch,pr):
    import urllib2
    import numpy as np
    str1='https://netfiles.umn.edu/users/nacht001/www/nachtsheim/Kutner/Chapter%20%20'   
    # chapter number 
    if(ch<10): 
        ch_str=str(ch).zfill(2)
    else:
        ch_str=str(ch)
    if(pr<10):
        pr_str=str(pr).zfill(2)
    else:
        pr_str=str(pr)
    
    str2=str(ch)+'%20Data%20Sets/CH'+ch_str+'TA'+pr_str+'.txt'
    str3=str1+str2
    try: urllib2.urlopen(str3)
    except urllib2.URLError as e:
        print(e.reason), '\nChapter number or example number is wrong. Try again!'
        return np.array([])
    flink = urllib2.urlopen(str3)
    data=[]
    for line in flink: 
        lines=line.strip('\r\n'); lines=lines.split();
        data.append(lines) 
    flink.close()    
    colnos=len(data[0])
    j=0; xdata = np.zeros((len(data),colnos))
    for line in data:
        for k in range(0,colnos):
            xdata[j,k]=data[j][k]
        j=j+1
    return xdata 

Again one can save this function in the same file read_data_fx and can import it as follows:

from read_data_fx import read_tb_dataTA
data=read_tb_dataTA(3,4)

print data

[[ 125.  160.]
 [ 100.  112.]
 [ 200.  124.]
 [  75.   28.]
 [ 150.  152.]
 [ 175.  156.]
 [  75.   42.]
 [ 175.  124.]
 [ 125.  150.]
 [ 200.  104.]
 [ 100.  136.]]