Merge pull request #11 from DGrothe-PhD/dev

statistics calculation page using flask
DGrothe-PhD · May 15, 2024 · 8b576e5 · 8b576e5
2 parents cc75eed + a839fab
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diff --git a/Mathematics/Statistikberechnungen/StatisticCalc.py b/Mathematics/Statistikberechnungen/StatisticCalc.py
@@ -0,0 +1,83 @@
+#!/usr/bin/python
+from flask import Flask, render_template
+from flask import request
+from flask_table import Table, Col
+
+import ast
+import statistics as stats
+import numpy as np
+from py_markdown_table.markdown_table import markdown_table
+
+# initialization
+class QuantileTable(Table):
+    Name = Col('Name')
+    Average = Col('Mittelwert')
+    Minimum = Col('Min')
+    Quartile1 = Col('Q1')
+    Median = Col('Median')
+    Quartile3 = Col('Q3')
+    Maximum = Col('Max')
+
+
+
+# Run app
+app = Flask(__name__)
+
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+@app.route('/evalQuart', methods=['GET','POST'])
+def evalQuart():
+    result = ''
+    if request.method == 'POST':
+        raw_numbers = request.form['numbers']
+        numbers = list(ast.literal_eval(raw_numbers.strip("()[]{}")))
+        name = request.form['name']
+        result = EvaluateQuantiles(numbers, name)
+    elif request.method == 'GET':
+        pass
+    return render_template('index.html', tableofresults = result)
+
+# Calculus
+#example_data = [43.07, 39.23, 44.76, 42.15, 39.98, 40.5, 46.08, 38.62]
+
+
+def EvaluateQuantiles(data_list, name = ""):
+    # Sort first
+    original_data = data_list
+    data_list.sort()
+    sorted_data = data_list
+    print("sorted .... : ", sorted_data)
+    #
+    # Calculate quartiles
+    Q1 = np.percentile(original_data, 25)
+    Median = np.percentile(original_data, 50)
+    Q3 = np.percentile(original_data, 75)
+    Avg = stats.mean(original_data)
+    #
+    # Table
+    results = [
+        {
+            "Name": name,
+            "Average" : Avg,
+            "Minimum" : sorted_data[0],
+            "Quartile1" : Q1,
+            "Median" : Median,
+            "Quartile3": Q3,
+            "Maximum" : sorted_data[-1],
+
+        }
+    ]
+
+    tableofresults = QuantileTable(results)
+    #tableofresults = markdown_table(results).get_markdown()
+    return tableofresults
+
+# Example
+
+#EvaluateQuantiles(example_data, "Beispiel")
+
+
+if __name__ == '__main__':
+    app.run()
diff --git a/Mathematics/Statistikberechnungen/static/styles/mainpage.css b/Mathematics/Statistikberechnungen/static/styles/mainpage.css
@@ -0,0 +1,35 @@
+body{
+	font-family:Calibri;
+	font-size: 22px;
+}
+form, input, button{
+	font-size: 22px;
+}
+h1 { font-size: 52px; color: darkseagreen; }
+
+th,td{
+	text-align:right;
+	padding:0.5em;
+}
+
+th:nth-child(4),td:nth-child(4){
+	text-align:left;
+	padding-right:3em;
+}
+div{
+	margin-top:12pt;
+}
+thead{
+	background-color: darkseagreen;
+}
+
+table, th, td{
+	border: 1px solid gray;
+	border-collapse: collapse;
+}
+tr:nth-child(even){
+	background-color: lavender;
+}
+td:hover{
+	background-color: #e7e7e7;
+}
diff --git a/Mathematics/Statistikberechnungen/templates/index.html b/Mathematics/Statistikberechnungen/templates/index.html
@@ -0,0 +1,23 @@
+<!DOCTYPE html>
+<html>
+	<head>
+		<title>Statistikberechnungen</title>
+		<link rel= "stylesheet" type= "text/css" href= "{{ url_for('static',filename='styles/mainpage.css') }}">
+	</head>
+	<body>
+		<h1>Median und Quartil</h1>
+		<p>Aufgabe: Wir haben eine Zahlenreihe und sollen davon den Median und das erste und dritte Quartil berechnen.</p>
+		<form action='evalQuart' method='post'>
+			<label>Zahlenreihe eingeben (Dezimalpunkt, mit Komma getrennt)</label>
+			<input type='text' placeholder = 'Bezeichnung'
+				value='{{request.form.name}}'
+				name="name">
+			<input type='text' placeholder = 'Zahlenreihe'
+				value='{{request.form.numbers}}'
+				name="numbers">
+			<button type='submit'>Berechnen</button>
+
+			<div class="table">{{tableofresults}}</div>
+		</form>
+	</body>
+</html>