LabWork6 completed.

LabWork01/LabWork6/ConvertorDataFrame.py

@@ -1,6 +1,6 @@
 import pandas as pd
 
-def covertorDataFrame():
+def CovertorDataFrame():
 
     df = pd.read_csv("res/Stores.csv")
 
@@ -14,7 +14,7 @@ def covertorDataFrame():
         lambda x: 'Small_Area' if x <= 1100 else ('Average_Area' if 1100 < x <= 1700 else 'Big_Area'))
 
     mainDF['TextStoreSales'] = mainDF['Store_Sales'].apply(
-        lambda x: 'Small_Sales' if x <= 50000 else ('Average_Sales' if 50000 < x <= 80000 else 'Big_Sales'))
+        lambda x: 'Small_Sales' if x <= 50000 else ('Average_Sales' if 50000 < x <= 70000 else 'Big_Sales'))
 
     mainDF['TextDailyCustomerCount'] = mainDF['Daily_Customer_Count'].apply(
         lambda x: 'Small_Customer' if x <= 400 else ('Average_Customer' if 400 < x <= 900 else 'Big_Customer'))

LabWork01/LabWork6/ReservCopy/CopyTree.py

@@ -2,7 +2,7 @@ import math
 import pandas as pd
 from functools import reduce
 
-from LabWork01.LabWork6.ConvertorDataFrame import covertorDataFrame
+from LabWork01.LabWork6.ConvertorDataFrame import CovertorDataFrame
 
 # Дата сет
 # data = [
@@ -18,7 +18,7 @@ from LabWork01.LabWork6.ConvertorDataFrame import covertorDataFrame
 # df0 = pd.DataFrame(data)
 # df0.columns = ["цвет", "форма", "результат"]
 
-df0 = covertorDataFrame()[0]
+df0 = CovertorDataFrame()[0]
 
 # Лямбда-выражение для распределения значений, аргумент - pandas.Series,
 # возвращаемое значение - массив с количеством каждого из значений

LabWork01/LabWork6/Tree.py

@@ -1,19 +1,20 @@
 import math
 from functools import reduce
 
-from LabWork01.LabWork6.ConvertorDataFrame import covertorDataFrame
+from LabWork01.LabWork6.ConvertorDataFrame import CovertorDataFrame
 
 # дата-сет
-df0 = covertorDataFrame()[0]
+dfMain = CovertorDataFrame()[0]
+dfTest = CovertorDataFrame()[1]
 
 cstr = lambda s: [k + ":" + str(v) for k, v in sorted(s.value_counts().items())]
 
 # Структура данных Decision Tree
 tree = {
     # name: Название этого нода (узла)
-    "name": "decision tree " + df0.columns[-1] + " " + str(cstr(df0.iloc[:, -1])),
+    "name": "decision tree " + dfMain.columns[-1] + " " + str(cstr(dfMain.iloc[:, -1])),
     # df: Данные, связанные с этим нодом (узлом)
-    "df": df0,
+    "df": dfMain,
     # edges: Список ребер (ветвей), выходящих из этого узла, или пустой массив, если ниже нет листового узла.
     "edges": [],
 }
@@ -61,13 +62,37 @@ while (len(open) != 0):
     pass
 
 # Выводим дата сет
-print(df0, "\n-------------")
+print(dfMain, "\n-------------")
+
+# оценка тестовых данных
+def predict_bp(nodes, target) -> int:
+    overlap = None
+    for node in nodes:
+        check: bool = node["value"] == target[node["attr"]]
+        if check:
+            overlap = node
+            break
+    if overlap is None:
+        overlap = nodes[-1]
+    if len(overlap["edges"]) == 0:
+        return int(overlap["df"]["StoreSales"].mean())
+    else:
+        return predict_bp(overlap["edges"], target)
+
+def predict_str(count: int):
+    predictions = []
+    for i in range(count):
+        row = dfTest.iloc[i]
+        prediction = f"{ {'Age': row['Age'], 'BMI': row['BMI']} }" + \
+                     f"<br/>predict {predict_bp(tree['edges'], {'Age': row['Age'], 'BMI': row['BMI']})} / fact {row['BloodPressure']}"
+        predictions.append(prediction)
+    return '<br/>'.join(predictions)
 
 def tstr(tree, indent=""):
     s = indent + tree["name"] + str(cstr(tree["df"].iloc[:, -1]) if len(tree["edges"]) == 0 else "") + "\n"
     # Зацикливаем все ветви этого узла.
     for e in tree["edges"]:
-        s += tstr(e, indent + "  ")
+        s += tstr(e, "\t" + indent + "  ")
         pass
     return s
 

LabWork01/LoadDB.py

@@ -14,7 +14,7 @@ from LabWork01.LabWork3.CustomGraphics import createCusGraphics
 from LabWork01.LabWork3.DeletePng import deleteAllPng
 from LabWork01.LabWork4.SiteSearch import SiteSearch
 from LabWork01.LabWork5.create_plot import create_plot_jpg
-from LabWork01.LabWork6.ConvertorDataFrame import covertorDataFrame
+from LabWork01.LabWork6.ConvertorDataFrame import CovertorDataFrame
 from LabWork01.LabWork6.Tree import getStringTree
 
 app = Flask(__name__)
@@ -216,7 +216,7 @@ def get_plot_image():
 
 @app.route('/createTree', methods=['GET'])
 def get_data_Tree():
-    DataTree = getStringTree()
+    DataTree = getStringTree().split('\n')
 
     return render_template('tree_page.html', DataTree=DataTree)
 

LabWork01/templates/tree_page.html

@@ -23,7 +23,15 @@
         </div>
     </form>
     <div class="">
-            <p>{{ DataTree }}</p>
+        {% for item in DataTree %}
+            {% if item.count("\t") == 1 %}
+                <p  style="margin-left: 50px;"> {{ item }}</p>
+            {% elif item.count("\t") == 2 %}
+                <p  style="margin-left: 100px;"> {{ item }}</p>
+            {% else %}
+                <p>{{ item }}</p>
+            {% endif %}
+        {% endfor %}
     </div>
 </div>
 </body>