Lab work 2.

LabWork01/AnalysCustomers.py

@@ -0,0 +1,23 @@
+import pandas
+import pandas as pd
+
+def analysCustomersDataFrame(df: pandas.DataFrame):
+
+    df['Size'] = df['Store_Area'].apply(lambda x: 'Small' if x <= 1100 else ('Average' if 1100 < x <= 1800 else 'Big'))
+
+    table_one = df.query("Size == 'Small'").groupby('Size')
+    table_two = df.query("Size == 'Average'").groupby('Size')
+    table_three = df.query("Size == 'Big'").groupby('Size')
+
+    minMaxMean_one = table_one.agg({'Daily_Customer_Count': ['min', 'max', 'mean']}).round(2).reset_index()
+    minMaxMean_two = table_two.agg({'Daily_Customer_Count': ['min', 'max', 'mean']}).round(2).reset_index()
+    minMaxMean_three = table_three.agg({'Daily_Customer_Count': ['min', 'max', 'mean']}).round(2).reset_index()
+
+    totalTable = pd.merge(minMaxMean_one, minMaxMean_two, left_index=True, right_index=True)
+
+    totalTable = pd.merge(totalTable, minMaxMean_three, left_index=True, right_index=True)
+
+    # for data in roundedListShops.items():
+    #     roundedListShops.loc[data[0], 'Store_Area'] = (data[1].astype("Int64")/100)*100
+
+    return totalTable

LabWork01/AnalysSales.py

@@ -0,0 +1,23 @@
+import pandas
+import pandas as pd
+
+def analysSalesDataFrame(df: pandas.DataFrame):
+
+    df['Size'] = df['Store_Area'].apply(lambda x: 'Small' if x <= 1100 else ('Average' if 1100 < x <= 1800 else 'Big'))
+
+    table_one = df.query("Size == 'Small'").groupby('Size')
+    table_two = df.query("Size == 'Average'").groupby('Size')
+    table_three = df.query("Size == 'Big'").groupby('Size')
+
+    minMaxMean_one = table_one.agg({'Store_Sales': ['min', 'max', 'mean']}).round(2).reset_index()
+    minMaxMean_two = table_two.agg({'Store_Sales': ['min', 'max', 'mean']}).round(2).reset_index()
+    minMaxMean_three = table_three.agg({'Store_Sales': ['min', 'max', 'mean']}).round(2).reset_index()
+
+    totalTable = pd.merge(minMaxMean_one, minMaxMean_two, left_index=True, right_index=True)
+
+    totalTable = pd.merge(totalTable, minMaxMean_three, left_index=True, right_index=True)
+
+    # for data in roundedListShops.items():
+    #     roundedListShops.loc[data[0], 'Store_Area'] = (data[1].astype("Int64")/100)*100
+
+    return totalTable

LabWork01/AnalysSalesCustomers.py

@@ -0,0 +1,23 @@
+import pandas
+import pandas as pd
+
+def analysSalesCustomersDataFrame(df: pandas.DataFrame):
+
+    df['SaleCustomer'] = df['Daily_Customer_Count'].apply(lambda x: 'Small' if x <= 200 else ('Average' if 200 < x <= 800 else 'Big'))
+
+    table_one = df.query("SaleCustomer == 'Small'").groupby('SaleCustomer')
+    table_two = df.query("SaleCustomer == 'Average'").groupby('SaleCustomer')
+    table_three = df.query("SaleCustomer == 'Big'").groupby('SaleCustomer')
+
+    minMaxMean_one = table_one.agg({'Store_Sales': ['min', 'max', 'mean']}).round(2).reset_index()
+    minMaxMean_two = table_two.agg({'Store_Sales': ['min', 'max', 'mean']}).round(2).reset_index()
+    minMaxMean_three = table_three.agg({'Store_Sales': ['min', 'max', 'mean']}).round(2).reset_index()
+
+    totalTable = pd.merge(minMaxMean_one, minMaxMean_two, left_index=True, right_index=True)
+
+    totalTable = pd.merge(totalTable, minMaxMean_three, left_index=True, right_index=True)
+
+    # for data in roundedListShops.items():
+    #     roundedListShops.loc[data[0], 'Store_Area'] = (data[1].astype("Int64")/100)*100
+
+    return totalTable

LabWork01/DataFrameAnalys.py

@@ -0,0 +1,25 @@
+import pandas
+import pandas as pd
+
+#или как analysDataFrame(df)->pandas.DataFrame:
+
+def analysItemsDataFrame(df: pandas.DataFrame):
+
+    df['Size'] = df['Store_Area'].apply(lambda x: 'Small' if x <= 1100 else ('Average' if 1100 < x <= 1800 else 'Big'))
+
+    table_one = df.query("Size == 'Small'").groupby('Size')
+    table_two = df.query("Size == 'Average'").groupby('Size')
+    table_three = df.query("Size == 'Big'").groupby('Size')
+
+    minMaxMean_one = table_one.agg({'Items_Available': ['min', 'max', 'mean']}).round(2).reset_index()
+    minMaxMean_two = table_two.agg({'Items_Available': ['min', 'max', 'mean']}).round(2).reset_index()
+    minMaxMean_three = table_three.agg({'Items_Available': ['min', 'max', 'mean']}).round(2).reset_index()
+
+    totalTable = pd.merge(minMaxMean_one, minMaxMean_two, left_index=True, right_index=True)
+
+    totalTable = pd.merge(totalTable, minMaxMean_three, left_index=True, right_index=True)
+
+    # for data in roundedListShops.items():
+    #     roundedListShops.loc[data[0], 'Store_Area'] = (data[1].astype("Int64")/100)*100
+
+    return totalTable

LabWork01/FuncLoad.py

@@ -1,7 +1,4 @@
-import csv
-import numpy as np
 import pandas as pd
-from LabWork01.Shop import Shop
 
 def createDataFrame():
     df = pd.read_csv('../res/Stores.csv')

LabWork01/LoadDB.py

@@ -1,4 +1,9 @@
 from flask import Flask, redirect, url_for, request, render_template
+
+from LabWork01.AnalysCustomers import analysCustomersDataFrame
+from LabWork01.AnalysSales import analysSalesDataFrame
+from LabWork01.AnalysSalesCustomers import analysSalesCustomersDataFrame
+from LabWork01.DataFrameAnalys import analysItemsDataFrame
 from LabWork01.FuncLoad import createDataFrame
 
 app = Flask(__name__)
@@ -14,7 +19,7 @@ countNull = listShops.isnull().sum()
 
 @app.route("/")
 def home():
-    return render_template('main_page.html', context=[], listTypes=listTypes, countNull=countNull, firstRow=1, secondRow=4, firstColumn=1, secondColumn=4)
+    return render_template('main_page.html', context=[], tableAnalys=[], titles=[''], listTypes=listTypes, countNull=countNull, firstRow=1, secondRow=4, firstColumn=1, secondColumn=4)
 
 @app.route("/showDiapason", methods=['GET','POST'])
 def numtext():
@@ -61,17 +66,23 @@ def numtext():
 #функция для проведения анализа данных
 @app.route("/analysis", methods=['GET', 'POST'])
 def analysis():
+    firstAnalys = analysItemsDataFrame(listShops)
 
-    roundedListShops = listShops
+    secondAnalys = analysCustomersDataFrame(listShops)
 
-    for data in roundedListShops.items():
-        roundedListShops.loc[data[0], 'Store_Area'] = (data[1].astype("Int64")/100)*100
+    thirdAnalys = analysSalesDataFrame(listShops)
 
-    #groupingByArea = listShops.groupby(['Store_Area']/100*100).agg({'Items_Available': ['mean']})
+    fourthAnalys = analysSalesCustomersDataFrame(listShops)
 
-    print(roundedListShops)
+    print(firstAnalys)
 
-    return home()
+    return render_template('main_page.html', context=[], tableAnalysOne=[firstAnalys.to_html()],
+                           tableAnalysTwo=[secondAnalys.to_html()],
+                           tableAnalysThree=[thirdAnalys.to_html()],
+                           tableAnalysFour=[fourthAnalys.to_html()],
+                           titles=[''],
+                           listTypes=listTypes, countNull=countNull, firstRow=1,
+                           secondRow=4, firstColumn=1, secondColumn=4)
 
 if __name__=="__main__":
     app.run(debug=True)

LabWork01/templates/main_page.html

@@ -52,5 +52,49 @@
             {% endfor %}
         </table>
     </div>
+    <div>
+        <h3>
+            Результаты первого анализа
+        </h3>
+        <h1>
+            {% for table in tableAnalysOne %}
+            <h2>{{ titles[loop.index] }}</h2>
+            {{ table|safe }}
+            {% endfor %}
+        </h1>
+    </div>
+    <div>
+        <h3>
+            Результаты второго анализа
+        </h3>
+        <h1>
+            {% for table in tableAnalysTwo %}
+            <h2>{{ titles[loop.index] }}</h2>
+            {{ table|safe }}
+            {% endfor %}
+        </h1>
+    </div>
+    <div>
+        <h3>
+            Результаты третьего анализа
+        </h3>
+        <h1>
+            {% for table in tableAnalysThree %}
+            <h2>{{ titles[loop.index] }}</h2>
+            {{ table|safe }}
+            {% endfor %}
+        </h1>
+    </div>
+    <div>
+        <h3>
+            Результаты четвёртого анализа
+        </h3>
+        <h1>
+            {% for table in tableAnalysFour %}
+            <h2>{{ titles[loop.index] }}</h2>
+            {{ table|safe }}
+            {% endfor %}
+        </h1>
+    </div>
 </body>
 </html>