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_one.columns = minMaxMean_one.columns.droplevel()
    minMaxMean_two = table_two.agg({'Store_Sales': ['min', 'max', 'mean']}).round(2).reset_index()
    minMaxMean_two.columns = minMaxMean_two.columns.droplevel()
    minMaxMean_two = minMaxMean_two.iloc[:, 1:4]
    minMaxMean_three = table_three.agg({'Store_Sales': ['min', 'max', 'mean']}).round(2).reset_index()
    minMaxMean_three.columns = minMaxMean_three.columns.droplevel()
    minMaxMean_three = minMaxMean_three.iloc[:, 1:4]

    df1 = pd.DataFrame()
    df1['small'] = minMaxMean_one['min']
    df1['average'] = minMaxMean_two['min']
    df1['big'] = minMaxMean_three['min']

    df2 = pd.DataFrame()
    df2['small'] = minMaxMean_one['max']
    df2['average'] = minMaxMean_two['max']
    df2['big'] = minMaxMean_three['max']

    df3 = pd.DataFrame()
    df3['small'] = minMaxMean_one['mean']
    df3['average'] = minMaxMean_two['mean']
    df3['big'] = minMaxMean_three['mean']

    totalTable = [df1, df2, df3]

    return totalTable