Member Avatar for Ri0o

hi, i'm new in python programming
i'm trying to write a simple program that processes a text file containing grades for a class, extracts the desired grades, count the number of grades in each grade segment and genrate a pie chart for grades,(A1) and here is the text file link
http://pages.cpsc.ucalgary.ca/~zongpeng ... rades1.txt
any help would be appreciated

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Dani AI

Generated

A concise, practical plan to get from the attached text file to the counts you need for a pie chart: identify which column holds the numeric score, skip the header and any trailer/EOF marker, convert scores to numbers (strip percent signs if present), map each numeric score to a grade bucket, and count occurrences (then convert counts to percentages or angles for QuickDraw). This builds on suggestions from , and the observation by that the file uses tab-separated rows and contains a header plus an EOF marker. (daniweb.com)

Use a tolerant parser (splitting on whitespace handles tabs) and guard conversions with try/except so malformed lines get skipped instead of crashing the program. The example below shows a compact, reusable approach: a function to map a numeric score to a label, a parser that finds the score column by index, and a Counter to tally buckets.

from collections import Counter

def grade_label(score, cutoffs):
    for thresh, label in cutoffs:
        if score >= thresh:
            return label
    return cutoffs[-1][1]

def parse_counts(path, grade_index, cutoffs):
    counts = Counter()
    with open(path, 'r') as f:
        next(f, None)             # skip header
        for line in f:
            s = line.strip()
            if not s or s.lower().startswith('end') or 'eof' in s.lower():
                continue
            parts = s.split()     # handles tabs and spaces
            try:
                raw = parts[grade_index].rstrip('%')
                score = float(raw)
            except (IndexError, ValueError):
                continue
            counts[grade_label(score, cutoffs)] += 1
    return counts

Choose cutoffs as a descending list, e.g. [(90,'A'),(80,'B'),(70,'C'),(60,'D'),(0,'F')]. To feed QuickDraw, compute angles with angle = count/total * 360 (one angle per label) or percentages with count/total*100. Quick checks: print header.split() and the first data line to confirm the grade_index, handle percent signs or trailing text, and watch for BOM/encoding or CRLF issues when opening old files. These steps produce robust counts you can pass straight to your pie-drawing routine.

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All 7 Replies

Member Avatar for Mathhax0r

Assuming you already know how to read in from files, there's a wonderful plotting tool for python called matplotlib that will let you make your pie chart. You'll have to get numpy first, though.

Btw, your link to the text file is broken.

Edited by Mathhax0r because: n/a
Member Avatar for Stefano Mtangoo

try using link at the top toolbar of your editor. Very helpful to post links.
As buddy said, Matplotlib+wxPython will give you total control. If you do simple plotting, then wxPython have tool for that.

Anyway what do yo want to do with grades? May be python-mysql+wxPython+Matplotlib is all you need

Member Avatar for Ri0o

unfortunatly i'm only allowed to use quickdraw,
i'm only struggling in figuring out how to extract the data from the txt file and assign the numbers to grades ,count how many scored each grade, i know how to make the chart (A1)
http://pages.cpsc.ucalgary.ca/~zongpeng/CPSC231/assignments/A3/grades1.txt
any help or tips would be appreciated

Edited by Ri0o because: n/a
Member Avatar for Stefano Mtangoo

Ok, do us a favour,
attach that file to your post. Jus Click reply and you will see button to attach and do it. We cant know the content of the file!

Do it please :)

Member Avatar for Stefano Mtangoo

I missed the Link to the file.
As far as I can see, you need to look at csv module to help you to do it.
What I propose is:
1. Open file
2. Get contents of one line
3. get that line with delimiter set to space ie ' '
4. Do whatever you want with data
NB: you can print the result to see what it produces before you use the data. Remember to use:

csv.reader(open('grades1.txt'), delimiter=' ')

More links:
http://docs.python.org/library/csv.html

http://tinyurl.com/yf3pqka
Hope it helps

Member Avatar for vegaseat

Actually. your raw data file is tab delimited and easily converted into a list of lists. Once that is done you can simply access your specific data by index and looping through the list.

The only special considerations are that the first line is a header and the last line is an 'end of file' marker.

Member Avatar for Ri0o
hi, i'm new in python programming i'm trying to write a simple program that processes a text file containing grades for a class, extracts the desired grades, count the number of grades in each grade segment and genrate a pie chart for grades,(A1) . any help would be appreciated

ID	Last	First	Lecture	Tutor	A1	A2	A3	A4	A5
6882621	Lee	Lisa	LO1	TO7	2.0	7.0	1.0	10.0	8.5
5727139	Lee	John	LO1	TO8	3.5	3.5	8.5	0.0	2.0
4592442	Jones	Linda	LO0	TO7	8.0	7.5	3.5	1.5	2.0
4194804	Bing	Robert	LO1	TO0	1.5	8.0	3.5	9.5	8.0
3841058	Johnson	Paul	LO1	TO6	9.0	2.0	8.0	9.5	2.0
3378161	Freeman	John	LO1	TO3	2.0	6.0	8.5	8.5	9.5
5140629	Thomas	Helen	LO0	TO4	0.0	2.0	9.0	10.0	2.0
9347090	Miller	Maria	LO1	TO1	9.5	9.5	6.5	8.0	9.0
1916293	Jones	Robert	LO1	TO4	8.5	0.5	10.0	2.0	3.5
6353341	Miller	Lisa	LO0	TO2	2.0	2.5	3.0	9.0	7.5
7594201	Johnson	Linda	LO0	TO6	7.0	6.0	6.0	2.0	9.5
9529592	Freeman	John	LO0	TO3	3.0	9.5	8.5	10.0	9.0
7123952	Moore	Maria	LO0	TO4	6.5	6.0	5.5	9.0	3.5
5784699	Thomas	Maria	LO1	TO3	1.5	8.0	9.0	1.0	8.0
7009346	Davis	Helen	LO1	TO9	1.5	2.0	9.0	1.0	2.0
2235041	Bing	James	LO1	TO4	6.5	9.0	8.5	9.5	2.5
9295242	Freeman	Paul	LO1	TO5	6.5	9.5	1.0	4.0	10.0
7501126	Miller	Maria	LO0	TO0	8.5	3.0	10.0	8.5	8.0
3971527	Davis	Maria	LO0	TO9	9.0	1.5	2.5	3.5	1.5
0084475	Miller	John	LO1	TO7	8.5	1.5	9.0	2.5	1.0
2167228	Freeman	James	LO1	TO5	4.5	8.5	9.5	8.5	10.0
3031060	Freeman	Robert	LO0	TO9	6.5	9.0	10.0	9.0	3.0
5598222	Bing	Lisa	LO0	TO9	6.5	2.5	8.0	6.0	0.5
7543280	Lee	Mary	LO1	TO8	9.5	9.0	8.5	9.5	1.0
6483388	Thomas	Linda	LO1	TO3	5.5	6.0	1.5	3.0	1.0
3751752	Miller	Maria	LO1	TO8	9.5	1.5	2.5	9.5	9.0
4395813	Freeman	James	LO1	TO9	3.5	10.0	5.0	6.5	2.5
0410097	Davis	John	LO0	TO2	3.5	8.0	0.5	9.0	2.0
3719104	Davis	Mary	LO0	TO0	1.0	1.5	4.5	3.5	10.0
9959266	Freeman	Helen	LO0	TO0	8.0	9.0	1.5	7.5	1.5
6861532	Jones	Maria	LO0	TO2	1.0	3.5	4.5	4.0	2.5
8304781	Johnson	Helen	LO0	TO6	10.0	9.0	8.0	10.0	7.5
5337432	Taylor	James	LO1	TO7	1.5	9.0	9.5	2.5	3.5
2602852	Davis	Lisa	LO0	TO3	1.0	7.5	5.5	1.5	2.0
4293362	Miller	Robert	LO1	TO7	9.5	4.5	8.5	8.0	8.5
0158170	Lee	John	LO1	TO1	1.5	3.5	2.5	1.0	9.0
6576801	Jones	David	LO1	TO6	9.5	4.0	9.5	9.0	10.0
5761759	Lee	Robert	LO0	TO6	2.5	2.0	9.0	8.0	2.0
9009383	Johnson	Paul	LO0	TO9	2.0	8.0	2.5	9.5	10.0
9519864	Taylor	John	LO0	TO4	7.5	2.5	8.5	2.5	10.0
1824451	Taylor	James	LO0	TO6	9.5	4.5	9.0	8.5	9.0
0423903	Taylor	Lisa	LO0	TO3	3.0	3.0	3.5	1.5	0.0
9300493	Jones	Mary	LO1	TO6	10.0	9.0	9.5	9.0	9.5
6429383	Jones	Mary	LO1	TO3	10.0	8.5	9.0	2.5	9.0
6389950	Lee	Robert	LO1	TO2	8.5	5.0	1.0	7.0	2.0
8625509	Thomas	Mary	LO0	TO3	2.0	7.0	8.0	3.0	9.0
3953468	Freeman	David	LO0	TO9	8.0	8.5	1.0	2.5	2.5
7743437	Bing	Linda	LO0	TO3	0.0	7.0	8.5	9.5	8.5
4306782	Jones	Linda	LO0	TO5	2.0	9.5	3.5	7.5	9.5
6299607	Miller	James	LO0	TO8	8.5	5.0	7.5	9.5	2.0
8295182	Davis	Linda	LO0	TO9	9.5	9.5	2.5	8.0	8.0
4849291	Freeman	Helen	LO0	TO5	8.5	2.0	9.5	3.0	8.5
7658018	Thomas	Paul	LO1	TO2	9.0	8.0	8.5	2.5	9.0
3028404	Jones	Paul	LO0	TO4	8.5	10.0	6.0	2.0	9.0
1063070	Miller	John	LO0	TO0	10.0	3.0	4.0	8.0	3.0
0899667	Jones	Mary	LO1	TO6	2.0	2.0	9.0	10.0	8.0
8459165	Moore	John	LO1	TO4	2.5	2.5	8.5	1.0	9.5
7503479	Jones	Mary	LO1	TO3	5.5	8.0	8.5	8.5	10.0
2806139	Miller	Paul	LO1	TO6	9.5	3.5	9.5	9.5	9.0
5357396	Miller	David	LO1	TO2	9.5	0.5	8.5	3.0	8.0
2400621	Miller	James	LO0	TO4	2.0	10.0	3.0	9.5	1.5
7199745	Taylor	Maria	LO1	TO4	2.0	10.0	6.5	8.0	3.5
7375539	Freeman	Mary	LO0	TO8	10.0	8.0	7.0	3.0	8.0
7300880	Jones	Robert	LO0	TO8	2.0	2.0	1.0	9.5	6.0
1332697	Freeman	David	LO1	TO4	8.0	7.0	1.0	8.5	2.0
3284906	Thomas	Maria	LO1	TO4	2.5	1.5	3.5	9.0	9.5
5411217	Jones	Lisa	LO0	TO4	10.0	2.5	10.0	9.0	3.5
0896946	Moore	Lisa	LO1	TO2	2.5	8.0	7.5	1.5	10.0
7207189	Lee	Mary	LO1	TO1	8.5	1.0	10.0	10.0	0.0
1243134	Davis	John	LO1	TO6	1.5	10.0	2.0	2.0	10.0
4463744	Taylor	Paul	LO0	TO8	0.0	1.5	9.5	0.0	8.0
4662506	Miller	Helen	LO1	TO6	7.0	10.0	1.5	9.5	8.0
3983380	Davis	James	LO1	TO9	3.5	8.0	8.0	5.0	8.5
3123601	Freeman	Robert	LO1	TO2	8.5	8.5	9.0	8.5	1.5
2965912	Bing	Linda	LO0	TO7	2.0	9.0	8.0	9.0	8.0
7195536	Lee	Paul	LO1	TO2	1.0	1.0	8.5	2.5	8.0
1886035	Davis	Paul	LO1	TO1	8.0	8.0	1.5	6.5	10.0
3932253	Thomas	Mary	LO1	TO5	9.0	9.0	4.5	3.5	6.0
5847220	Bing	Paul	LO1	TO9	8.5	3.0	8.0	2.5	10.0
4532923	Jones	Robert	LO0	TO5	2.5	1.5	10.0	9.0	9.5
1881752	Johnson	Helen	LO1	TO3	2.5	3.5	8.5	2.5	2.0
0834763	Davis	John	LO0	TO5	9.0	3.5	9.0	8.0	8.5
4786795	Miller	Maria	LO0	TO3	8.0	8.0	8.0	8.0	4.5
7685892	Thomas	Lisa	LO1	TO6	3.5	1.5	2.5	7.5	9.0
2798090	Jones	John	LO0	TO3	8.5	2.0	6.5	2.0	10.0
9609974	Jones	Linda	LO1	TO9	6.5	7.0	9.0	3.5	8.5
2357750	Thomas	Linda	LO0	TO8	2.5	8.5	1.0	1.0	3.0
1813468	Lee	John	LO1	TO3	10.0	1.5	5.5	8.5	10.0
3863617	Moore	Mary	LO0	TO4	2.0	9.5	2.0	10.0	6.5
7366878	Bing	David	LO0	TO1	1.5	2.5	10.0	3.5	2.0
8991569	Bing	Linda	LO1	TO9	1.0	3.0	7.5	8.0	8.5
9882308	Thomas	Helen	LO1	TO9	9.5	2.0	8.5	10.0	3.5
5973710	Bing	Robert	LO0	TO8	2.0	9.0	9.0	0.0	2.0
0097002	Thomas	David	LO0	TO7	8.0	9.0	8.0	2.0	9.5
3275773	Johnson	Mary	LO0	TO3	10.0	8.5	3.0	9.5	8.5
3183649	Freeman	Mary	LO0	TO5	1.0	10.0	3.5	9.5	3.0
5055095	Freeman	Maria	LO1	TO8	2.5	1.0	8.5	8.5	9.0
0785510	Bing	Robert	LO1	TO8	9.5	1.5	1.5	2.5	3.5
9497502	Taylor	Mary	LO1	TO6	9.0	9.5	8.5	1.5	8.0
7167053	Johnson	James	LO0	TO3	9.0	10.0	9.5	1.0	3.5
0724716	Taylor	Helen	LO1	TO6	9.5	9.0	2.5	2.0	10.0
5745865	Freeman	Helen	LO0	TO2	6.0	9.0	2.5	10.0	6.5
5865892	Johnson	Robert	LO0	TO0	9.0	9.0	8.0	0.0	2.0
8097087	Taylor	Helen	LO1	TO3	2.0	1.5	9.0	9.0	3.5
8707595	Miller	Helen	LO0	TO8	1.5	8.5	9.5	3.0	2.5
3099178	Jones	Maria	LO1	TO2	3.0	10.0	2.0	2.5	2.5
6944872	Taylor	David	LO1	TO0	1.0	7.5	9.0	8.5	9.5
1359192	Davis	Linda	LO0	TO0	3.5	10.0	6.0	9.5	6.0
0303445	Taylor	Robert	LO0	TO4	8.5	8.5	3.5	3.0	8.0
9484561	Davis	Lisa	LO1	TO4	8.0	4.0	1.0	9.5	9.0
7084062	Davis	Mary	LO0	TO1	9.5	9.5	3.5	6.5	7.5
1571681	Miller	Maria	LO0	TO1	1.5	8.0	10.0	8.0	10.0
5036203	Davis	Helen	LO1	TO8	10.0	9.5	3.0	1.0	6.0
3882721	Thomas	Paul	LO0	TO4	9.0	1.5	1.0	3.0	8.0
0891727	Johnson	Helen	LO0	TO9	2.5	10.0	9.5	2.5	4.5
4769088	Miller	John	LO1	TO5	3.5	2.0	3.0	8.0	3.0
4628171	Davis	Mary	LO1	TO6	3.5	10.0	2.5	6.5	1.0
6522044	Lee	Lisa	LO0	TO5	10.0	9.0	1.5	9.5	3.0
8513443	Johnson	James	LO1	TO9	1.0	7.0	1.5	9.0	1.0
2191126	Freeman	Robert	LO0	TO5	2.5	8.0	3.0	7.5	0.5
0122422	Thomas	Paul	LO1	TO9	8.5	10.0	2.0	9.0	2.5
4535365	Moore	Robert	LO0	TO4	8.0	9.0	1.0	8.5	1.0
9478146	Moore	Robert	LO0	TO5	9.0	10.0	2.5	3.5	2.5
7430187	Taylor	Mary	LO0	TO9	3.5	2.5	8.5	2.0	8.5
0420782	Jones	Paul	LO1	TO5	5.0	2.5	9.5	1.0	1.5
9216671	Bing	Robert	LO0	TO3	9.0	9.5	2.5	3.0	10.0
5680965	Freeman	Lisa	LO1	TO2	1.0	2.0	1.0	4.0	1.5
1561226	Jones	Helen	LO0	TO3	10.0	8.5	10.0	10.0	7.0
5800880	Taylor	John	LO0	TO2	2.0	9.5	8.0	8.5	2.0
4745064	Lee	Robert	LO0	TO8	1.0	9.0	7.5	9.5	9.5
0124905	Thomas	Robert	LO0	TO5	0.0	6.0	7.5	3.0	8.5
9412148	Moore	Helen	LO1	TO3	2.5	10.0	10.0	4.5	8.0
1651802	Lee	James	LO1	TO9	3.0	9.0	7.0	8.0	0.0
2966435	Taylor	John	LO1	TO4	3.5	2.0	8.0	2.0	1.0
6418425	Jones	Paul	LO0	TO3	10.0	3.0	9.0	8.0	3.0
3938727	Johnson	John	LO1	TO9	9.0	6.0	4.0	8.5	9.5
4174757	Thomas	John	LO1	TO9	2.0	8.0	2.5	10.0	10.0
7311720	Davis	John	LO1	TO4	8.5	9.0	1.0	2.5	9.0
8208044	Miller	James	LO1	TO3	2.0	3.0	9.0	3.5	2.0
5523808	Miller	Maria	LO0	TO1	3.5	9.0	8.0	9.5	5.0
9568715	Davis	David	LO0	TO5	8.0	1.5	2.0	9.0	1.0
7210843	Bing	David	LO1	TO1	9.0	3.0	8.5	9.0	1.5
0982498	Freeman	Robert	LO0	TO9	3.5	2.5	2.5	1.5	8.0
7993288	Moore	David	LO0	TO0	9.5	10.0	1.5	1.0	1.5
8400573	Johnson	Lisa	LO0	TO1	2.0	1.5	9.5	9.5	6.0
2750734	Jones	James	LO0	TO7	2.5	1.0	10.0	6.5	8.0
2226816	Lee	Lisa	LO1	TO5	6.0	5.5	3.0	2.0	9.5
5908017	Bing	Paul	LO1	TO1	9.5	1.5	9.5	3.0	1.0
5701656	Davis	David	LO1	TO8	9.0	2.5	1.5	8.5	9.5
2899468	Davis	James	LO1	TO4	4.0	2.5	7.5	2.5	9.5
2445411	Davis	Linda	LO1	TO5	8.5	10.0	3.5	2.5	7.5
7156143	Thomas	David	LO0	TO1	5.0	3.5	9.5	10.0	8.5
0278356	Thomas	Mary	LO1	TO1	0.0	3.5	10.0	8.0	10.0
3305129	Taylor	Paul	LO1	TO6	9.0	6.0	9.0	6.0	8.0
2241172	Johnson	John	LO1	TO7	2.0	3.0	8.0	8.0	9.0
7518221	Thomas	Mary	LO1	TO4	9.5	8.0	8.0	7.5	3.0
6937962	Freeman	John	LO0	TO9	8.0	3.5	1.0	1.5	3.5
3138608	Lee	John	LO0	TO1	3.0	10.0	9.0	1.0	9.5
0622474	Jones	Maria	LO1	TO7	2.0	8.0	5.5	8.0	9.5
3162261	Taylor	Linda	LO0	TO1	9.0	1.0	8.5	9.0	1.0
6317075	Miller	David	LO1	TO3	8.5	7.5	2.5	9.5	9.0
4594585	Miller	Lisa	LO1	TO3	9.5	9.0	3.0	9.0	2.5
8677663	Miller	Paul	LO1	TO0	9.5	4.0	3.5	9.0	10.0
2118002	Thomas	Lisa	LO1	TO9	0.5	9.5	9.0	2.0	9.5
6255739	Johnson	David	LO1	TO2	9.5	3.0	2.5	2.5	3.5
2894340	Thomas	Paul	LO0	TO0	8.5	9.0	7.0	9.0	2.5
9491631	Miller	Paul	LO1	TO9	8.5	2.5	7.5	9.0	9.5
0070081	Lee	Paul	LO1	TO1	2.5	10.0	1.0	9.5	3.5
3982776	Taylor	Helen	LO1	TO8	1.5	1.0	1.5	1.0	9.0
6210665	Freeman	John	LO0	TO8	10.0	1.0	2.5	7.0	8.0
8157366	Moore	Paul	LO0	TO1	9.5	10.0	8.5	10.0	9.5
3723339	Taylor	Linda	LO1	TO1	2.0	9.5	3.5	8.5	8.5
6526727	Thomas	Lisa	LO1	TO4	10.0	10.0	8.0	8.5	8.0
6478890	Lee	Linda	LO0	TO2	2.5	7.0	2.0	2.0	2.5
9642989	Johnson	Helen	LO0	TO7	9.0	0.0	1.0	9.5	10.0
9369429	Jones	James	LO0	TO8	1.5	10.0	1.0	9.0	9.5
4280640	Moore	Helen	LO0	TO4	3.0	9.0	9.5	9.0	9.0
0057063	Jones	Mary	LO1	TO9	8.0	7.5	3.0	1.5	9.0
0279761	Lee	Helen	LO1	TO7	1.0	7.0	1.0	9.5	3.0
1940836	Davis	Lisa	LO0	TO9	1.5	3.5	4.5	8.0	2.5
6359035	Miller	James	LO0	TO2	10.0	3.0	9.5	3.0	8.5
6178303	Freeman	Mary	LO0	TO4	9.5	9.5	3.0	8.0	1.5
4531622	Lee	Helen	LO0	TO0	8.5	2.0	10.0	9.5	6.0
3152656	Jones	Robert	LO1	TO4	1.5	8.0	7.0	2.5	1.5
1942257	Davis	Mary	LO0	TO9	9.5	8.5	3.5	9.5	3.5
4910827	Lee	John	LO0	TO6	8.0	7.0	3.5	2.0	2.0
7998296	Jones	Linda	LO1	TO1	2.0	9.0	9.0	10.0	9.0
1876861	Bing	Lisa	LO1	TO8	2.0	9.0	7.0	3.0	1.5
2968691	Thomas	David	LO0	TO7	8.0	8.5	4.5	3.5	8.5
2281437	Jones	Mary	LO0	TO0	9.0	2.5	4.5	4.5	9.5
5367989	Lee	James	LO0	TO1	3.5	3.5	8.0	9.0	6.5
2702361	Miller	John	LO0	TO4	10.0	1.5	5.5	1.0	1.0
9204661	Freeman	Paul	LO0	TO6	2.0	3.5	2.5	9.5	9.0
9175403	Jones	David	LO0	TO8	8.0	3.0	4.5	2.0	1.0
0380188	Davis	John	LO0	TO5	10.0	9.5	9.5	1.0	8.5
4646732	Thomas	Maria	LO1	TO3	9.0	4.0	7.0	2.5	2.0
3102045	Thomas	Linda	LO0	TO7	3.0	8.5	2.5	9.0	9.5
7037617	Thomas	Paul	LO1	TO1	2.5	2.0	2.0	7.0	5.0
2209727	Jones	David	LO0	TO3	2.0	3.5	10.0	8.0	5.5
4193846	Freeman	Linda	LO0	TO8	9.5	3.5	9.0	9.0	8.5
EOF
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