36 lines
1.4 KiB
Python
36 lines
1.4 KiB
Python
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_one.columns = minMaxMean_one.columns.droplevel()
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minMaxMean_two = table_two.agg({'Daily_Customer_Count': ['min', 'max', 'mean']}).round(2).reset_index()
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minMaxMean_two.columns = minMaxMean_two.columns.droplevel()
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minMaxMean_three = table_three.agg({'Daily_Customer_Count': ['min', 'max', 'mean']}).round(2).reset_index()
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minMaxMean_three.columns = minMaxMean_three.columns.droplevel()
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df1 = pd.DataFrame()
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df1['small'] = minMaxMean_one['min']
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df1['average'] = minMaxMean_two['min']
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df1['big'] = minMaxMean_three['min']
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df2 = pd.DataFrame()
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df2['small'] = minMaxMean_one['max']
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df2['average'] = minMaxMean_two['max']
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df2['big'] = minMaxMean_three['max']
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df3 = pd.DataFrame()
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df3['small'] = minMaxMean_one['mean']
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df3['average'] = minMaxMean_two['mean']
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df3['big'] = minMaxMean_three['mean']
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totalTable = [df1, df2, df3]
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return totalTable |