Numeri/plots.py

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2022-09-22 15:15:32 +00:00
from io import BytesIO
from flask import Flask, render_template
# app = Flask("Project Numeri")
from flask import Flask, make_response, request
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.figure import Figure
import base64
# app = Flask(__name__)
GRADE_LIST = "Cijfers-HerrewijnenJonathan.csv"
print(GRADE_LIST)
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def plot():
# Generate the figure **without using pyplot**.
fig = Figure()
ax = fig.subplots()
ax.plot([1, 2])
# Save it to a temporary buffer.
buf = BytesIO()
fig.savefig(buf, format="png")
# Embed the result in the html output.
data = base64.b64encode(buf.getbuffer()).decode("ascii")
return f"<img src='data:image/png;base64,{data}'/>"
# import pandas as pd
# import numpy as np
# class Cijferlijst:
# def __init__(self, grade_list=GRADE_LIST):
# self.grade_list = grade_list
# self.ps = pd.read_csv(GRADE_LIST, skiprows=2, sep=';')
# '''
# Get all data from a subject and a (yearly) period:
# GetSubjectByYear("godsdienst", "2010/2011")
# '''
# def GetSubjectByYear(self, subject, year):
# if(type(subject) == str and type(year) == str):
# select_year = self.ps[self.ps['Schooljaar(Voortgangsdossier)'] == year]
# select_subject = select_year[select_year["Vak(Voortgangsdossier)"] == subject]
# #filter period and rapport
# rapports = select_subject[select_subject['Cijfertype(Voortgangsdossier)'] != "Periodegemiddelde"]
# return rapports[rapports ['Cijfertype(Voortgangsdossier)'] != "Rapportcijfer"]
# else:
# return False
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# def iets(self):
# print(self.grade_list)
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# def CalculateMedian(self, subject, year):
# # Calculates average for all scores without weight!
# Grades = self.ps['Cijfer(Voortgangsdossier)'].loc[:]