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# Working with Data Files¶

So far, the data we have used in this book have all been either coded right into the program, or have been entered by the user. In real life data reside in files. For example the images we worked with in the image processing unit ultimately live in files on your hard drive. Web pages, and word processing documents, and music are other examples of data that live in files. In this short chapter we will introduce the Python concepts necessary to use data from files in our programs.

For our purposes, we will assume that our data files are text files–that is, files filled with characters. The Python programs that you write are stored as text files. We can create these files in any of a number of ways. For example, we could use a text editor to type in and save the data. We could also download the data from a website and then save it in a file. Regardless of how the file is created, Python will allow us to manipulate the contents.

In Python, we must open files before we can use them and close them when we are done with them. As you might expect, once a file is opened it becomes a Python object just like all other data. Table 1 shows the methods that can be used to open and close files.

Method Name Use Explanation
open open(filename,'r') Open a file called filename and use it for reading. This will return a reference to a file object.
open open(filename,'w') Open a file called filename and use it for writing. This will also return a reference to a file object.
close filevariable.close() File use is complete.

## Finding a File on your Disk¶

Opening a file requires that you, as a programmer, and Python agree about the location of the file on your disk. The way that files are located on disk is by their path You can think of the filename as the short name for a file, and the path as the full name. For example on a Mac if you save the file hello.txt in your home directory the path to that file is /Users/yourname/hello.txt On a Windows machine the path looks a bit different but the same principles are in use. For example on windows the path might be C:\Users\yourname\My Documents\hello.txt

You can access files in folders, also called directories, under your home directory by adding a slash and the name of the folder. For example we have been storing files to use with PyCharm in the CS150 folder inside the PyCharmProjects folder under your home directory. The full name for hello.py stored in the CS150 folder would be /Users/yourname/PyCharmProjects/CS150/hello.py

Here’s the important rule to remember: If your file and your Python program are in the same directory you can simply use the filename. open('myfile.txt','r') If your file and your Python program are in different directories then you should use the path to the file open(/Users/joebob01/myfile.txt).

## Reading a File¶

As an example, suppose we have a text file called qbdata.txt that contains the following data representing statistics about NFL quarterbacks. Although it would be possible to consider entering this data by hand each time it is used, you can imagine that it would be time-consuming and error-prone to do this. In addition, it is likely that there could be data from more quarterbacks and other years. The format of the data file is as follows

`First Name, Last Name, Position, Team, Completions, Attempts, Yards, TDs Ints, Comp%, Rating`
```Colt McCoy QB, CLE  135 222 1576    6   9   60.8%   74.5
Josh Freeman QB, TB 291 474 3451    25  6   61.4%   95.9
Michael Vick QB, PHI    233 372 3018    21  6   62.6%   100.2
Matt Schaub QB, HOU 365 574 4370    24  12  63.6%   92.0
Philip Rivers QB, SD    357 541 4710    30  13  66.0%   101.8
Matt Hasselbeck QB, SEA 266 444 3001    12  17  59.9%   73.2
Jimmy Clausen QB, CAR   157 299 1558    3   9   52.5%   58.4
Joe Flacco QB, BAL  306 489 3622    25  10  62.6%   93.6
Kyle Orton QB, DEN  293 498 3653    20  9   58.8%   87.5
Jason Campbell QB, OAK  194 329 2387    13  8   59.0%   84.5
Peyton Manning QB, IND  450 679 4700    33  17  66.3%   91.9
Drew Brees QB, NO   448 658 4620    33  22  68.1%   90.9
Matt Ryan QB, ATL   357 571 3705    28  9   62.5%   91.0
Matt Cassel QB, KC  262 450 3116    27  7   58.2%   93.0
Mark Sanchez QB, NYJ    278 507 3291    17  13  54.8%   75.3
Brett Favre QB, MIN 217 358 2509    11  19  60.6%   69.9
David Garrard QB, JAC   236 366 2734    23  15  64.5%   90.8
Eli Manning QB, NYG 339 539 4002    31  25  62.9%   85.3
Carson Palmer QB, CIN   362 586 3970    26  20  61.8%   82.4
Alex Smith QB, SF   204 342 2370    14  10  59.6%   82.1
Chad Henne QB, MIA  301 490 3301    15  19  61.4%   75.4
Tony Romo QB, DAL   148 213 1605    11  7   69.5%   94.9
Jay Cutler QB, CHI  261 432 3274    23  16  60.4%   86.3
Jon Kitna QB, DAL   209 318 2365    16  12  65.7%   88.9
Tom Brady QB, NE    324 492 3900    36  4   65.9%   111.0
Ben Roethlisberger QB, PIT  240 389 3200    17  5   61.7%   97.0
Kerry Collins QB, TEN   160 278 1823    14  8   57.6%   82.2
Derek Anderson QB, ARI  169 327 2065    7   10  51.7%   65.9
Ryan Fitzpatrick QB, BUF    255 441 3000    23  15  57.8%   81.8
Donovan McNabb QB, WAS  275 472 3377    14  15  58.3%   77.1
Kevin Kolb QB, PHI  115 189 1197    7   7   60.8%   76.1
Aaron Rodgers QB, GB    312 475 3922    28  11  65.7%   101.2
Sam Bradford QB, STL    354 590 3512    18  15  60.0%   76.5
Shaun Hill QB, DET  257 416 2686    16  12  61.8%   81.3
```

To open this file, we would call the open function. The variable, fileref, now holds a reference to the file object returned by open. When we are finished with the file, we can close it by using the close method. After the file is closed any further attempts to use fileref will result in an error.

```>>>fileref = open("qbdata.txt","r")
>>>
>>>fileref.close()
>>>
```

### Iterating over lines in a file¶

We will now use this file as input in a program that will do some data processing. In the program, we will read each line of the file and print it with some additional text. Because text files are sequences of lines of text, we can use the for loop to iterate through each line of the file.

A line of a file is defined to be a sequence of characters up to and including a special character called the newline character. If you evaluate a string that contains a newline character you will see the character represented as \n. If you print a string that contains a newline you will not see the \n, you will just see its effects. When you are typing a Python program and you press the enter or return key on your keyboard, the editor inserts a newline character into your text at that point.

As the for loop iterates through each line of the file the loop variable will contain the current line of the file as a string of characters. The general pattern for processing each line of a text file is as follows:

```for line in myFile:
    statement1
    statement2
    ...
```

To process all of our quarterback data, we will use a for loop to iterate over the lines of the file. Using the split method, we can break each line into a list containing all the fields of interest about the quarterback. We can then take the values corresponding to first name, lastname, and passer rating to construct a simple sentence as shown in Listing 1.

(files_for)

```
```

### Alternative File Reading Methods¶

In addition to the for loop, Python provides three methods to read data from the input file. The readline method reads one line from the file and returns it as a string. The string returned by readline will contain the newline character at the end. This method returns the empty string when it reaches the end of the file. The readlines method returns the contents of the entire file as a list of strings, where each item in the list represents one line of the file. It is also possible to read the entire file into a single string with read. Table 2 summarizes these methods and Session 2 shows them in action.

Note that we need to reopen the file before each read so that we start from the beginning. Each file has a marker that denotes the current read position in the file. Any time one of the read methods is called the marker is moved to the character immediately following the last character returned. In the case of readline this moves the marker to the first character of the next line in the file. In the case of read or readlines the marker is moved to the end of the file.

```>>> infile = open("qbdata.txt","r")
>>> aline = infile.readline()
>>> aline
'Colt McCoy QB, CLE\t135\t222\t1576\t6\t9\t60.8%\t74.5\n'
>>>
>>> infile = open("qbdata.txt","r")
>>> linelist = infile.readlines()
>>> print(len(linelist))
34
>>> print(linelist[0:4])
['Colt McCoy QB, CLE\t135\t222\t1576\t6\t9\t60.8%\t74.5\n',
 'Josh Freeman QB, TB\t291\t474\t3451\t25\t6\t61.4%\t95.9\n',
 'Michael Vick QB, PHI\t233\t372\t3018\t21\t6\t62.6%\t100.2\n',
 'Matt Schaub QB, HOU\t365\t574\t4370\t24\t12\t63.6%\t92.0\n']
>>>
>>> infile = open("qbdata.txt","r")
>>> filestring = infile.read()
>>> print(len(filestring))
1708
>>> print(filestring[:256])
Colt McCoy QB, CLE  135     222     1576    6       9       60.8%   74.5
Josh Freeman QB, TB 291     474     3451    25      6       61.4%   95.9
Michael Vick QB, PHI        233     372     3018    21      6       62.6%   100.2
Matt Schaub QB, HOU 365     574     4370    24      12      63.6%   92.0
Philip Rivers QB, SD        357     541     4710    30      13      66.0%   101.8
Matt Ha
>>>
```
Method Name Use Explanation
write filevar.write(astring) Add astring to the end of the file. filevar must refer to a file that has been opened for writing.
read(n) filevar.read() Reads and returns a string of n characters, or the entire file as a single string if n is not provided.
readline(n) filevar.readline() Returns the next line of the file with all text up to and including the newline character. If n is provided as a parameter than only n characters will be returned if the line is longer than n.
readlines(n) filevar.readlines() Returns a list of strings, each representing a single line of the file. If n is not provided then all lines of the file are returned. If n is provided then n characters are read but n is rounded up so that an entire line is returned.

Now lets look at another method of reading our file using a while loop. This important because many other programming languages do not support the for loop style for reading file but they do support the pattern we’ll show you here.

(files_while)

```
```

The important thing to notice is that on line two we have the statement line = infile.readline() This is very important because the while condition needs to have a value for the line variable. We call this initial read the priming read.

### Glossary¶

open
You must open a file before you can read its contents.
close
When you are done with a file, you should close it.
read
Will read the entire contents of a file as a string. This is often used in an assignment statement so that a variable can reference the contents of the file.
readline
Will read a single line from the file, up to and including the first instance of the newline character.
readlines
Will read the entire contents of a file into a list where each line of the file is a string and is an element in the list.

### Exercises¶

The following sample file contains one line for each student in an imaginary class the students name is the first thing on each line, followed by some exam scores.

```joe 10 15 20 30 40
bill 23 16 19 22
sue 8 22 17 14 32 17 24 21 2 9 11 17
grace 12 28 21 45 26 10
john 14 32 25 16 89
```
1. Using the text file student_data.dat write a program that prints out the names of students that have more than six quiz scores.

2. Using the text file student_data.dat write a program that calculates the average grade for each student, and print out the student’s name along with their average grade.

3. Using the text file student_data.dat write a program that calculates the minimum and maximum grade grade for each student. Print out the students name along with their minimum and maximum scores.

Here is a file called lab_data.dat that contains some sample data from a lab experiment.

```44 71
79 37
78 24
41 76
19 12
19 32
28 36
22 58
89 92
91 6
53 7
27 80
14 34
8 81
80 19
46 72
83 96
88 18
96 48
77 67
    ```
1. Using the data file lab_data.data each line contains a an x,y coordinate pair.

Write a function called plotRegression that reads the data from this file and uses a turtle to plot those points and a best fit line according to the following formulas

$y = \bar{y} + m(x - \bar{x})$$m = \frac{\sum{x_iy_i - n\bar{x}\bar{y}}}{\sum{x_i^2}-n\bar{x}^2}$

Where $$\bar{x}$$ is the mean of the x-values, $$\bar{y}$$ is the mean of the y- values and $$n$$ is the number of points. If you are not familiar with the mathematical $$\sum$$ it is the sum operation. For example $$\sum{x_i}$$ means to add up all the x values.

Your program should analyze the points and correctly scale the window using setworldcoordinates so that that each point can be plotted. Then you should draw the best fit line, in a different color, through the points.

1. At the end of this chapter is a very long file called mystery.dat The lines of this file contain either the word UP or DOWN or a pair of numbers. UP and DOWN are instructions for a turtle to lift up or put down its tail. The pair of numbers are some x,y coordinates. Write a program that reads the file mystery.dat and uses the turtle to draw the picture described by the commands and the set of points.

```UP
-218 185
DOWN
-240 189
-246 188
-248 183
-246 178
-244 175
-240 170
-235 166
-229 163
-220 158
-208 156
-203 153
-194 148
-187 141
-179 133
-171 119
-166 106
-163 87
-161 66
-162 52
-164 44
-167 28
-171 6
-172 -15
-171 -30
-165 -46
-156 -60
-152 -67
-152 -68
UP
-134 -61
DOWN
-145 -66
-152 -78
-152 -94
-157 -109
-157 -118
-151 -128
-146 -135
-146 -136
UP
-97 -134
DOWN
-98 -138
-97 -143
-96 -157
-96 -169
-98 -183
-104 -194
-110 -203
-114 -211
-117 -220
-120 -233
-122 -243
-123 -247
-157 -248
-157 -240
-154 -234
-154 -230
-153 -229
-149 -226
-146 -223
-145 -219
-143 -214
-142 -210
-141 -203
-139 -199
-136 -192
-132 -184
-130 -179
-132 -171
-133 -162
-134 -153
-138 -145
-143 -137
-143 -132
-142 -124
-138 -112
-134 -104
-132 -102
UP
-97 -155
DOWN
-92 -151
-91 -147
-89 -142
-89 -135
-90 -129
-90 -128
UP
-94 -170
DOWN
-83 -171
-68 -174
-47 -177
-30 -172
-15 -171
-11 -170
UP
12 -96
DOWN
9 -109
9 -127
7 -140
5 -157
9 -164
22 -176
37 -204
40 -209
49 -220
55 -229
57 -235
57 -238
50 -239
49 -241
51 -248
53 -249
63 -245
70 -243
57 -249
62 -250
71 -250
75 -250
81 -250
86 -248
86 -242
84 -232
85 -226
81 -221
77 -211
73 -205
67 -196
62 -187
58 -180
51 -171
47 -164
46 -153
50 -141
53 -130
54 -124
57 -112
56 -102
55 -98
UP
48 -164
DOWN
54 -158
60 -146
64 -136
64 -131
UP
5 -152
DOWN
1 -150
-4 -145
-8 -138
-14 -128
-19 -119
-17 -124
UP
21 -177
DOWN
14 -176
7 -174
-6 -174
-14 -170
-19 -166
-20 -164
UP
-8 -173
DOWN
-8 -180
-5 -189
-4 -201
-2 -211
-1 -220
-2 -231
-5 -238
-8 -241
-9 -244
-7 -249
6 -247
9 -248
16 -247
21 -246
24 -241
27 -234
27 -226
27 -219
27 -209
27 -202
28 -193
28 -188
28 -184
UP
-60 -177
DOWN
-59 -186
-57 -199
-56 -211
-59 -225
-61 -233
-65 -243
-66 -245
-73 -246
-81 -246
-84 -246
-91 -245
-91 -244
-88 -231
-87 -225
-85 -218
-85 -211
-85 -203
-85 -193
-88 -185
-89 -180
-91 -175
-92 -172
-93 -170
UP
-154 -93
DOWN
-157 -87
-162 -74
-168 -66
-172 -57
-175 -49
-178 -38
-178 -26
-178 -12
-177 4
-175 17
-172 27
-168 36
-161 48
-161 50
UP
-217 178
DOWN
-217 178
-217 177
-215 176
-214 175
-220 177
-223 178
-223 178
-222 178
UP
-248 185
DOWN
-245 184
-240 182
-237 181
-234 179
-231 177
-229 176
-228 175
-226 174
-224 173
-223 173
-220 172
-217 172
-216 171
-214 170
-214 169
UP
-218 186
DOWN
-195 173
-183 165
-175 159
-164 151
-158 145
-152 139
-145 128
-143 122
-139 112
-138 105
-134 95
-131 88
-129 78
-126 67
-125 62
-125 54
-124 44
-125 38
-126 30
-125 27
-125 8
-126 5
-125 -9
-122 -15
-115 -25
-109 -32
-103 -39
-95 -42
-84 -45
-72 -47
-56 -48
-41 -47
-31 -46
-18 -45
-1 -44
9 -43
34 -45
50 -52
67 -61
83 -68
95 -80
112 -97
142 -115
180 -132
200 -146
227 -159
259 -175
289 -185
317 -189
349 -190
375 -191
385 -192
382 -196
366 -199
352 -204
343 -204
330 -205
315 -209
296 -212
276 -214
252 -208
237 -202
218 -197
202 -193
184 -187
164 -179
147 -173
128 -168
116 -164
102 -160
88 -158
78 -159
69 -162
57 -164
56 -165
51 -165
UP
68 -144
DOWN
83 -143
96 -141
109 -139
119 -146
141 -150
161 -155
181 -163
195 -169
208 -179
223 -187
241 -191
247 -193
249 -194
UP
-6 -141
DOWN
-15 -146
-29 -150
-42 -154
-51 -153
-60 -152
-60 -152
UP
-90 -134
DOWN
-85 -131
-79 -128
-78 -123
-80 -115
-82 -106
-80 -101
-76 -101
UP
-81 -132
DOWN
-76 -130
-71 -126
-72 -124
UP
43 -118
DOWN
44 -125
47 -135
41 -156
37 -160
40 -166
47 -171
47 -171
UP
-106 -153
DOWN
-107 -167
-106 -178
-109 -192
-114 -198
-116 -201
```
mystery.dat
{"extraction_info": {"found_math": true, "script_math_tex": 0, "script_math_asciimath": 0, "math_annotations": 0, "math_alttext": 0, "mathml": 0, "mathjax_tag": 0, "mathjax_inline_tex": 2, "mathjax_display_tex": 5, "mathjax_asciimath": 0, "img_math": 0, "codecogs_latex": 0, "wp_latex": 0, "mimetex.cgi": 0, "/images/math/codecogs": 0, "mathtex.cgi": 0}, "config": {"markdown_headings": true, "markdown_code": true, "boilerplate_config": {"ratio_threshold": 0.18, "absolute_threshold": 10, "end_threshold": 15, "enable": true}, "remove_buttons": true, "remove_image_figures": true, "remove_link_clusters": true, "table_config": {"min_rows": 2, "min_cols": 3, "format": "github"}, "remove_chinese": true, "remove_edit_buttons": true, "extract_latex": true}, "english_confidence": 0.9225728511810303, "perplexity_flag": "middle"}