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from IPython.display import HTML
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#The usual imports
import math
import glob
import os
from collections import OrderedDict
from pandas import read_csv
import numpy as np
from pymatgen.util.plotting import pretty_plot
from monty.string import remove_non_ascii
import seaborn as sns
import matplotlib.pyplot as plt
import datetime
%matplotlib inline
print("Last updated on %s" % datetime.datetime.today())
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# Load data from exported CSV from Ted Full Grade Center.
# Some sanitization is performed to remove non-ascii characters and cruft.
files = glob.glob(os.path.join(os.environ["CENG114GC"], "*.csv"))
latest = sorted(files)[-1]
d = read_csv(latest)
d.columns = [remove_non_ascii(c) for c in d.columns]
d.columns = [c.split("[")[0].strip().strip("\"") for c in d.columns]
d = d.fillna(0)
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# Define lower grade cutoffs in terms of number of standard deviations from mean.
grade_cutoffs = OrderedDict()
grade_cutoffs["A+"] = 1.5
grade_cutoffs["A"] = 1.0
grade_cutoffs["A-"] = 0.75
grade_cutoffs["B+"] = 0.5
grade_cutoffs["B"] = 0
grade_cutoffs["B-"] = -0.5
grade_cutoffs["C+"] = -0.75
grade_cutoffs["C"] = -1
grade_cutoffs["C-"] = -1.5
grade_cutoffs["F"] = float("-inf")
print("The cutoffs are:")
for k, v in grade_cutoffs.items():
print(u"%s: > μ + %.2f σ" % (k, v))
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# Define some general functions for computing grade statistics.
def bar_plot(dframe, data_key, offset=0, annotate=True, cutoffs=None):
"""
Creates a historgram of the results.
Args:
dframe: DataFrame which is imported from CSV.
data_key: Specific column to plot
offset: Allows an offset for each grade. Defaults to 0.
Returns:
dict of cutoffs, {grade: (lower, upper)}
"""
data = dframe[data_key]
d = [d for d in data if (not np.isnan(d)) and d != 0]
heights, bins = np.histogram(d, bins=20, range=(0, 100))
import matplotlib.pyplot as plt
sns.distplot(d, bins=np.arange(0, 105, 5), kde=False, rug=True)
plt = pretty_plot(12, 8, plt)
plt.xlabel("Score")
plt.ylabel("Number of students")
mean = np.mean(d)
sigma = np.std(d)
maxy = np.max(heights) + 5
prev_cutoff = 100
if cutoffs is None:
cutoffs = {}
grade = ["A", "B+", "B", "B-", "C+", "C", "C-", "F"]
for grade, cutoff in grade_cutoffs.items():
if cutoff == float("-inf"):
cutoff = 0
else:
cutoff = max(0, mean + cutoff * sigma) + offset
if annotate:
plt.plot([cutoff] * 2, [0, maxy], 'k--')
plt.annotate("%.2f" % cutoff, [cutoff, maxy - 1], fontsize=18, horizontalalignment='left', rotation=45)
n = len([d for d in data if cutoff <= d < prev_cutoff])
#print "Grade %s (%.1f-%.1f): %d" % (grade, cutoff, prev_cutoff, n)
if annotate:
plt.annotate(grade, [(cutoff + prev_cutoff) / 2, maxy], fontsize=18, horizontalalignment='center')
cutoffs[grade] = (cutoff, prev_cutoff)
prev_cutoff = cutoff
else:
cutoffs = {k: (v[0] + offset, v[1] + offset) for k, v in cutoffs.items()}
for grade, cutoff in cutoffs.items():
if annotate:
plt.plot([cutoff[0]] * 2, [0, maxy], 'k--')
plt.annotate("%.2f" % cutoff[0], [cutoff[0], maxy - 1], fontsize=18, horizontalalignment='left', rotation=45)
plt.annotate(grade, [(cutoff[0] + cutoff[1]) / 2, maxy], fontsize=18, horizontalalignment='center')
plt.xlim([0, 100])
plt.ylim([0, maxy * 1.1])
plt.annotate('$\\mu = %.2f$\n$\\sigma = %.2f$\n$max=%.2f$' % (mean, sigma, data.max()), xy=(10, 7), fontsize=30)
title = data_key.split("[")[0].strip()
plt.title(title, fontsize=30)
plt.tight_layout()
# plt.savefig("%s.png" % title)
return cutoffs
def assign_grades(d, column_name, cutoffs):
def compute_grade(pts):
for g, c in cutoffs.items():
if c[0] < pts <= c[1]:
return g
d["Final_Assigned_Egrade"] = [compute_grade(v) for v in d[column_name]]
d.to_csv(os.path.join(os.path.join(os.environ["CENG114GC"], "Overall grades %s.csv" % datetime.datetime.today().date())))
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cutoffs = bar_plot(d, "PS1", annotate=False)
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cutoffs = bar_plot(d, "CS1", annotate=False)
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cutoffs = bar_plot(d, "PS2", annotate=False)
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cutoffs = bar_plot(d, "CS2", annotate=False)
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cutoffs = bar_plot(d, "PS3", annotate=False)
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cutoffs = bar_plot(d, "CS3", annotate=False)
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cutoffs = bar_plot(d, "PS4", annotate=False)
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cutoffs = bar_plot(d, "CS4", annotate=False)
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cutoffs = bar_plot(d, "PS5", annotate=False)
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cutoffs = bar_plot(d, "CS5", annotate=False)
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cutoffs = bar_plot(d, "MT1", annotate=True)
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cutoffs = bar_plot(d, "MT2", annotate=True)
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cutoffs = bar_plot(d, "Final", annotate=True)
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cutoffs = bar_plot(d, "Weighted Total", annotate=True)
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cutoffs = bar_plot(d, "Final Total", offset=-1.93548, cutoffs=cutoffs, annotate=True)
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# The command below is used to generate the overall grade assignments for all students and dump it into a CSV file.
# assign_grades(d, "Final Total", cutoffs=cutoffs)