Lab work 2.
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ElEgEv
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LabWork01/AnalysCustomers.py
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LabWork01/AnalysCustomers.py
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import pandas
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import pandas as pd
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def analysCustomersDataFrame(df: pandas.DataFrame):
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df['Size'] = df['Store_Area'].apply(lambda x: 'Small' if x <= 1100 else ('Average' if 1100 < x <= 1800 else 'Big'))
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table_one = df.query("Size == 'Small'").groupby('Size')
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table_two = df.query("Size == 'Average'").groupby('Size')
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table_three = df.query("Size == 'Big'").groupby('Size')
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minMaxMean_one = table_one.agg({'Daily_Customer_Count': ['min', 'max', 'mean']}).round(2).reset_index()
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minMaxMean_two = table_two.agg({'Daily_Customer_Count': ['min', 'max', 'mean']}).round(2).reset_index()
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minMaxMean_three = table_three.agg({'Daily_Customer_Count': ['min', 'max', 'mean']}).round(2).reset_index()
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totalTable = pd.merge(minMaxMean_one, minMaxMean_two, left_index=True, right_index=True)
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totalTable = pd.merge(totalTable, minMaxMean_three, left_index=True, right_index=True)
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# for data in roundedListShops.items():
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# roundedListShops.loc[data[0], 'Store_Area'] = (data[1].astype("Int64")/100)*100
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return totalTable
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LabWork01/AnalysSales.py
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LabWork01/AnalysSales.py
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import pandas
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import pandas as pd
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def analysSalesDataFrame(df: pandas.DataFrame):
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df['Size'] = df['Store_Area'].apply(lambda x: 'Small' if x <= 1100 else ('Average' if 1100 < x <= 1800 else 'Big'))
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table_one = df.query("Size == 'Small'").groupby('Size')
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table_two = df.query("Size == 'Average'").groupby('Size')
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table_three = df.query("Size == 'Big'").groupby('Size')
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minMaxMean_one = table_one.agg({'Store_Sales': ['min', 'max', 'mean']}).round(2).reset_index()
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minMaxMean_two = table_two.agg({'Store_Sales': ['min', 'max', 'mean']}).round(2).reset_index()
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minMaxMean_three = table_three.agg({'Store_Sales': ['min', 'max', 'mean']}).round(2).reset_index()
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totalTable = pd.merge(minMaxMean_one, minMaxMean_two, left_index=True, right_index=True)
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totalTable = pd.merge(totalTable, minMaxMean_three, left_index=True, right_index=True)
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# for data in roundedListShops.items():
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# roundedListShops.loc[data[0], 'Store_Area'] = (data[1].astype("Int64")/100)*100
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return totalTable
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LabWork01/AnalysSalesCustomers.py
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LabWork01/AnalysSalesCustomers.py
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import pandas
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import pandas as pd
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def analysSalesCustomersDataFrame(df: pandas.DataFrame):
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df['SaleCustomer'] = df['Daily_Customer_Count'].apply(lambda x: 'Small' if x <= 200 else ('Average' if 200 < x <= 800 else 'Big'))
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table_one = df.query("SaleCustomer == 'Small'").groupby('SaleCustomer')
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table_two = df.query("SaleCustomer == 'Average'").groupby('SaleCustomer')
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table_three = df.query("SaleCustomer == 'Big'").groupby('SaleCustomer')
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minMaxMean_one = table_one.agg({'Store_Sales': ['min', 'max', 'mean']}).round(2).reset_index()
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minMaxMean_two = table_two.agg({'Store_Sales': ['min', 'max', 'mean']}).round(2).reset_index()
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minMaxMean_three = table_three.agg({'Store_Sales': ['min', 'max', 'mean']}).round(2).reset_index()
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totalTable = pd.merge(minMaxMean_one, minMaxMean_two, left_index=True, right_index=True)
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totalTable = pd.merge(totalTable, minMaxMean_three, left_index=True, right_index=True)
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# for data in roundedListShops.items():
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# roundedListShops.loc[data[0], 'Store_Area'] = (data[1].astype("Int64")/100)*100
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return totalTable
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LabWork01/DataFrameAnalys.py
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LabWork01/DataFrameAnalys.py
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import pandas
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import pandas as pd
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#или как analysDataFrame(df)->pandas.DataFrame:
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def analysItemsDataFrame(df: pandas.DataFrame):
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df['Size'] = df['Store_Area'].apply(lambda x: 'Small' if x <= 1100 else ('Average' if 1100 < x <= 1800 else 'Big'))
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table_one = df.query("Size == 'Small'").groupby('Size')
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table_two = df.query("Size == 'Average'").groupby('Size')
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table_three = df.query("Size == 'Big'").groupby('Size')
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minMaxMean_one = table_one.agg({'Items_Available': ['min', 'max', 'mean']}).round(2).reset_index()
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minMaxMean_two = table_two.agg({'Items_Available': ['min', 'max', 'mean']}).round(2).reset_index()
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minMaxMean_three = table_three.agg({'Items_Available': ['min', 'max', 'mean']}).round(2).reset_index()
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totalTable = pd.merge(minMaxMean_one, minMaxMean_two, left_index=True, right_index=True)
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totalTable = pd.merge(totalTable, minMaxMean_three, left_index=True, right_index=True)
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# for data in roundedListShops.items():
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# roundedListShops.loc[data[0], 'Store_Area'] = (data[1].astype("Int64")/100)*100
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return totalTable
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@ -1,7 +1,4 @@
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import csv
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import numpy as np
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import pandas as pd
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from LabWork01.Shop import Shop
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def createDataFrame():
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df = pd.read_csv('../res/Stores.csv')
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@ -1,4 +1,9 @@
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from flask import Flask, redirect, url_for, request, render_template
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from LabWork01.AnalysCustomers import analysCustomersDataFrame
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from LabWork01.AnalysSales import analysSalesDataFrame
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from LabWork01.AnalysSalesCustomers import analysSalesCustomersDataFrame
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from LabWork01.DataFrameAnalys import analysItemsDataFrame
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from LabWork01.FuncLoad import createDataFrame
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app = Flask(__name__)
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@ -14,7 +19,7 @@ countNull = listShops.isnull().sum()
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@app.route("/")
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def home():
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return render_template('main_page.html', context=[], listTypes=listTypes, countNull=countNull, firstRow=1, secondRow=4, firstColumn=1, secondColumn=4)
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return render_template('main_page.html', context=[], tableAnalys=[], titles=[''], listTypes=listTypes, countNull=countNull, firstRow=1, secondRow=4, firstColumn=1, secondColumn=4)
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@app.route("/showDiapason", methods=['GET','POST'])
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def numtext():
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@ -61,17 +66,23 @@ def numtext():
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#функция для проведения анализа данных
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@app.route("/analysis", methods=['GET', 'POST'])
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def analysis():
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firstAnalys = analysItemsDataFrame(listShops)
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roundedListShops = listShops
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secondAnalys = analysCustomersDataFrame(listShops)
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for data in roundedListShops.items():
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roundedListShops.loc[data[0], 'Store_Area'] = (data[1].astype("Int64")/100)*100
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thirdAnalys = analysSalesDataFrame(listShops)
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#groupingByArea = listShops.groupby(['Store_Area']/100*100).agg({'Items_Available': ['mean']})
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fourthAnalys = analysSalesCustomersDataFrame(listShops)
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print(roundedListShops)
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print(firstAnalys)
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return home()
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return render_template('main_page.html', context=[], tableAnalysOne=[firstAnalys.to_html()],
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tableAnalysTwo=[secondAnalys.to_html()],
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tableAnalysThree=[thirdAnalys.to_html()],
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tableAnalysFour=[fourthAnalys.to_html()],
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titles=[''],
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listTypes=listTypes, countNull=countNull, firstRow=1,
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secondRow=4, firstColumn=1, secondColumn=4)
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if __name__=="__main__":
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app.run(debug=True)
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@ -52,5 +52,49 @@
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{% endfor %}
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</table>
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</div>
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<div>
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<h3>
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Результаты первого анализа
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</h3>
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<h1>
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{% for table in tableAnalysOne %}
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<h2>{{ titles[loop.index] }}</h2>
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{{ table|safe }}
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{% endfor %}
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</h1>
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</div>
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<div>
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<h3>
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Результаты второго анализа
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</h3>
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<h1>
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{% for table in tableAnalysTwo %}
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<h2>{{ titles[loop.index] }}</h2>
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{{ table|safe }}
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{% endfor %}
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</h1>
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</div>
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<div>
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<h3>
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Результаты третьего анализа
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</h3>
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<h1>
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{% for table in tableAnalysThree %}
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<h2>{{ titles[loop.index] }}</h2>
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{{ table|safe }}
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{% endfor %}
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</h1>
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</div>
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<div>
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<h3>
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Результаты четвёртого анализа
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</h3>
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<h1>
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{% for table in tableAnalysFour %}
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<h2>{{ titles[loop.index] }}</h2>
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{{ table|safe }}
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{% endfor %}
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</h1>
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</div>
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</body>
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</html>
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