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canvasapp
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Merge branch 'master' of http://192.168.1.6/phowell/canvasapp

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Coding with Peter 2023-05-01 11:08:25 -07:00
parent 4520a53116 7696445ea0
commit aed354ad7f
1 changed files with 109 additions and 14 deletions
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123
stats.py
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@ -51,6 +51,33 @@ from collections import defaultdict
all_grades_file = f"cache/grades_all.csv"
all_courses_file = f"cache/course_grades_all.csv"
def sem_num_to_code(sem_num):
p = re.search(r'^(\d\d\d\d)(\d\d)$', sem_num)
if p:
yr = p.group(1)[2:4]
sem = p.group(2)
lookup = {'10':'wi','30':'sp', '50':'su', '70':'fa'}
return f"{lookup[sem]}{yr}"
return ""
def sem_code_to_num(sem_code): # fa23
p = re.search(r'^([a-z]{2})(\d\d)$', sem_code)
if p:
s = p.group(1)
y = p.group(2)
lookup = {'wi':'10','sp':'30', 'su':'50', 'fa':'70'}
return f"20{y}{lookup[s]}"
return ""
def codetest():
sems = '202330 202310 202270 202250 202230 202210 202170 202150 202130 202070 202050 202030 202010 201970 201950 201930 201910 201870 201850 201830'.split(' ')
codes = 'fa21 wi22 sp23 su23 fa23 wi24'.split(' ')
for s in sems:
print("{}: {}".format(s, sem_num_to_code(s)))
for c in codes:
print("{}: {}".format(c, sem_code_to_num(c)))
def get_all():
terms = '178 177 176 175 174 173 172 171 168 65 64 62 63 61 60 25 26 23 22 21'.split(' ')
sems = '202330 202310 202270 202250 202230 202210 202170 202150 202130 202070 202050 202030 202010 201970 201950 201930 201910 201870 201850 201830'.split(' ')
@ -120,7 +147,10 @@ def to_crn_fallback(name):
#print("Exception: ", e, name)
return None, None
def ilearn_name_to_course_code(iname):
parts = iname.split(' ')
code = parts[0]
return code
def short_name_to_crn(name):
#print(name)
@ -168,7 +198,27 @@ def short_name_to_teacher_type_crn_sem(name):
return None, None, None, None
pocrs = {}
def load_pocrs():
global pocrs
if not pocrs:
with open('cache/pocr_passed.csv') as csvfile:
csvreader = csv.reader(csvfile)
next(csvreader)
for row in csvreader:
pocrs[row[0] + " " + row[1]] = row[2]
return pocrs
def lookup_pocr(teacher,course,sem):
p = load_pocrs()
pcode = teacher + " " + course
if pcode in p:
sem_passed = sem_code_to_num(p[pcode])
sem_test = sem_code_to_num(sem)
if sem_passed < sem_test:
return True
return False
def nametest():
with open(all_courses_file) as csvfile:
@ -182,21 +232,22 @@ def nametest():
def above_70(li,maximum):
cutoff = 0.7 * maximum
above = list(filter(lambda x: x >= cutoff, li))
return (len(above)/len(li))
return round(len(above)/len(li), 3)
def process_one_course_grades(block, output):
def process_one_course_grades(block, output, teacher_to_code, course_to_code):
fxns = [mean, median, stdev, min, max, len]
c_id = block[0][0]
sem = block[0][1]
course_code = block[0][2]
cur_scores = [num(x[6]) for x in block]
final_scores = [num(x[7]) for x in block]
print(course_code)
teacher, mode, crn, sem2 = short_name_to_teacher_type_crn_sem(course_code)
if not teacher:
return
#print(cur_scores)
#print(final_scores)
tch_code = teacher_to_code[teacher]
crs_code = course_to_code[course_code]
if len(final_scores) < 2:
return
try:
(cur_mean, cur_median, cur_stdev, cur_min, cur_max, cur_count) = [round(f(cur_scores)) for f in fxns]
(final_mean, final_median, final_stdev, final_min, final_max, final_count) = [round(f(final_scores)) for f in fxns]
@ -204,19 +255,62 @@ def process_one_course_grades(block, output):
cur_pct_passed = above_70(cur_scores, cur_max)
final_pct_passed = above_70(final_scores, final_max)
print("Course % > 70 mean median stdev min max count")
print("{:>12} {: 6.0f} {: 6.0f} {: 6.0f} {: 6.0f} {: 6.0f} {: 6.0f} {:6d} ".format(course_code, cur_pct_passed, cur_mean, cur_median, cur_stdev, cur_min, cur_max, cur_count))
print("{:>12} {: 6.0f} {: 6.0f} {: 6.0f} {: 6.0f} {: 6.0f} {: 6.0f} {:6d} ".format(course_code, final_pct_passed, final_mean, final_median, final_stdev, final_min, final_max, final_count))
print()
if final_max == 0: return
scaled_final_scores = [ x / final_max for x in final_scores]
(scl_mean, scl_median, scl_stdev, scl_min, scl_max, scl_count) = [round(f(scaled_final_scores),2) for f in fxns]
good_code = ilearn_name_to_course_code(course_code)
pocr = 1 if lookup_pocr(teacher, good_code, sem2) else 0
#print("Course % > 70 mean median stdev min max count")
#print("{:>12} {: 6.0f} {: 6.0f} {: 6.0f} {: 6.0f} {: 6.0f} {: 6.0f} {:6d} ".format(course_code, cur_pct_passed, cur_mean, cur_median, cur_stdev, cur_min, cur_max, cur_count))
#print("{:>12} {: 6.0f} {: 6.0f} {: 6.0f} {: 6.0f} {: 6.0f} {: 6.0f} {:6d} ".format(course_code, final_pct_passed, final_mean, final_median, final_stdev, final_min, final_max, final_count))
#print()
#output.writerow( [sem2, crn, course_code, "current score", teacher, mode, cur_pct_passed, cur_mean, cur_median, cur_stdev, cur_min, cur_max, cur_count] )
output.writerow( [sem2, crn, course_code, "final score", teacher, mode, final_pct_passed, final_mean, final_median, final_stdev, final_min, final_max, final_count] )
#output.writerow( [crs_code, pocr, tch_code, mode, final_pct_passed, final_mean, final_median, final_stdev, final_min, final_max, scl_mean, scl_median, scl_stdev, scl_min, scl_max, final_count] )
output.writerow( [crs_code, good_code, pocr, tch_code, mode, final_pct_passed, scl_mean, scl_median, scl_stdev, scl_min, scl_max, final_count] )
except Exception as e:
print("Exception:", e)
def process_grades():
# first loop to get all names
courses_labeled = {}
teacher_to_code = {}
code_to_teacher = {}
course_to_code = {}
code_to_course = {}
index = 1001
crs_index = 4001
with open(all_grades_file, newline="") as csvfile:
csvreader = csv.reader(csvfile)
next(csvreader)
for row in csvreader:
crn_sem = row[0] + '_' + row[1]
if not crn_sem in courses_labeled:
teacher, mode, crn, sem2 = short_name_to_teacher_type_crn_sem(row[2])
courses_labeled[crn_sem] = teacher
if not row[2] in course_to_code:
course_to_code[row[2]] = crs_index
code_to_course[crs_index] = row[2]
crs_index += 1
if teacher:
if not teacher in teacher_to_code:
teacher_to_code[teacher] = index
code_to_teacher[index] = teacher
index += 1
codecs.open('cache/teacher_lookup_codes.json','w','utf-8').write( json.dumps( [teacher_to_code, code_to_teacher], indent=2) )
codecs.open('cache/course_lookup_codes.json','w','utf-8').write( json.dumps( [course_to_code, code_to_course], indent=2) )
with open(all_courses_file, "w", newline="") as output_f:
output = csv.writer(output_f)
output.writerow("sem crn shortname score_type teacher mode percent_passed mean median stdev min max count".split(" "))
output.writerow("course_code course pocr_status teacher_code mode percent_passed scl_mean scl_median scl_stdev scl_min scl_max count".split(" "))
with open(all_grades_file, newline="") as csvfile:
csvreader = csv.reader(csvfile)
@ -230,14 +324,14 @@ def process_grades():
if index != current_index:
if block:
process_one_course_grades(block, output)
process_one_course_grades(block, output, teacher_to_code, course_to_code)
block = []
current_index = index
block.append(row)
if block:
process_one_course_grades(block, output)
process_one_course_grades(block, output, teacher_to_code, course_to_code)
@ -247,6 +341,7 @@ if __name__ == "__main__":
options = { 1: ['get all historical grades from ilearn',get_all] ,
2: ['process grades csv file',process_grades] ,
3: ['test shortname parse',nametest] ,
4: ['test sem codes',codetest] ,
}
print ('')