KnowledgeBoat Logo
|

Informatics Practices

Write a program that stores the sales of 5 fast moving items of a store for each month in 12 Series objects, i.e., S1 Series object stores sales of these 5 items in 1st month, S2 stores sales of these 5 items in 2nd month, and so on.

The program should display the summary sales report like this :

Total Yearly Sales, item-wise (should display sum of items' sales over the months) 
Maximum sales of item made : <name of item that was sold the maximum in whole year> 
Maximum sales for individual items
Maximum sales of item 1 made : <month in which that item sold the maximum> 
Maximum sales of item 2 made : <month in which that item sold the maximum> 
Maximum sales of item 3 made : <month in which that item sold the maximum> 
Maximum sales of item 4 made : <month in which that item sold the maximum> 
Maximum sales of item 5 made : <month in which that item sold the maximum>

Python Pandas

1 Like

Answer

import pandas as pd
sales_data = {
    'Month_1': pd.Series([300, 250, 200, 150, 350], index=['Item_1', 'Item_2', 'Item_3', 'Item_4', 'Item_5']),
    'Month_2': pd.Series([380, 210, 220, 180, 320], index=['Item_1', 'Item_2', 'Item_3', 'Item_4', 'Item_5']),
    'Month_3': pd.Series([320, 270, 230, 200, 380], index=['Item_1', 'Item_2', 'Item_3', 'Item_4', 'Item_5']),
    'Month_4': pd.Series([310, 260, 210, 190, 360], index=['Item_1', 'Item_2', 'Item_3', 'Item_4', 'Item_5']),
    'Month_5': pd.Series([290, 240, 220, 170, 340], index=['Item_1', 'Item_2', 'Item_3', 'Item_4', 'Item_5']),
    'Month_6': pd.Series([300, 250, 400, 160, 350], index=['Item_1', 'Item_2', 'Item_3', 'Item_4', 'Item_5']),
    'Month_7': pd.Series([310, 260, 230, 180, 370], index=['Item_1', 'Item_2', 'Item_3', 'Item_4', 'Item_5']),
    'Month_8': pd.Series([320, 270, 240, 190, 380], index=['Item_1', 'Item_2', 'Item_3', 'Item_4', 'Item_5']),
    'Month_9': pd.Series([330, 280, 250, 200, 400], index=['Item_1', 'Item_2', 'Item_3', 'Item_4', 'Item_5']),
    'Month_10': pd.Series([340, 290, 260, 510, 420], index=['Item_1', 'Item_2', 'Item_3', 'Item_4', 'Item_5']),
    'Month_11': pd.Series([350, 300, 270, 220, 440], index=['Item_1', 'Item_2', 'Item_3', 'Item_4', 'Item_5']),
    'Month_12': pd.Series([360, 390, 280, 230, 260], index=['Item_1', 'Item_2', 'Item_3', 'Item_4', 'Item_5'])
}

sales_df = pd.DataFrame(sales_data)
print("Total Yearly Sales, item-wise:")
total_sales = sales_df.sum()
print(total_sales)

t = sales_df.sum(axis=1)
max_sales_item = t.idxmax()
print("\nMaximum sales of item made: ", max_sales_item)

print("\nMaximum sales for individual items:")
for item_num in range(1, 6):
    max_sales_month = None
    max_sales_value = 0
    for month in sales_df.columns:
        if sales_df[month][f'Item_{item_num}'] > max_sales_value:
            max_sales_value = sales_df[month][f'Item_{item_num}']
            max_sales_month = month
    print("Maximum sales of item", item_num, "made: ", max_sales_month)

Output

Total Yearly Sales, item-wise:
Month_1     1250
Month_2     1310
Month_3     1400
Month_4     1330
Month_5     1260
Month_6     1460
Month_7     1350
Month_8     1400
Month_9     1460
Month_10    1820
Month_11    1580
Month_12    1520
dtype: int64

Maximum sales of item made:  Item_5

Maximum sales for individual items:
Maximum sales of item 1 made: Month_2
Maximum sales of item 2 made: Month_12
Maximum sales of item 3 made: Month_6
Maximum sales of item 4 made: Month_10
Maximum sales of item 5 made: Month_11

Answered By

1 Like

Related Questions