Analysis of Sales dataset
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The document outlines an analysis of a sales dataset that includes data wrangling, analysis, and visualization using Google Sheets. Key findings include the total of 831 unique orders made from 2156 entries, the highest sales were in 2011, and the USA, Germany, Brazil, and France leading in sales numbers. The study also explores correlations between orders, products, and revenue, with price significantly influencing sales success across different products and companies.
Analysis of Sales dataset
- 1. Analysis of Sales Dataset Data wrangling, analysis and visualization using Google sheets platform.
- 2. Data Wrangling Data Wrangling Summary
- 3. 1. Data were into 8 rows (ID, OrderID, OrderDate, CompanyName, Country, Salesperson FirstName, Salespersion Surname, ProductName, ExtendedPrice). 2. Rows and columns were trimmed to remove any extra spaces that may complicate the analysis process. 3. First and second names of the salespersons merged to ease the analysis process. 4. Names were adjusted following the common rules of writing (first letter is capital and the rest is small). 5. Days, months, and years were extracted from the date columns to enable us doing thorough analysis over various time scales. 6. All of the data were concatenated to enable us run the duplicate fomula to ensure if there are any duplicate entries. 7. All of the data were gone through unique function as the same order may more than one product, so it give a false indication about the number of orders made. Data Wrangling Summary
- 4. Shape Number of rows 2156 Number of Null Values 0 Number of columns 11 Number of Duplicate Values 0 Header Count/Sum Comment Total Orders 831 Number of unique orders made as one order may contain more than one product. Companies 89 Number of companies involved. Countries 21 Number of countries where such operations were done. Total Salespersons 9 Number of sales reps who had done these operations. Total Products 1141 Number of unique products purchased through these operations Total revenue 1305792.8 7 Sum of the orders' revenue The above table highlights some statistics regarding our dataset where the total number of unique orders is 831 despite having 2156 entries, but the order may have more than one product under the same ID. In addition, we have a unique count of the other attributes such as companies, countries, sales reps, products and total revenue. Dataset Summary
- 5. The above charts demonstrate that number of orders made over different time scales. Over the years scale, 2011 witnessed the highest number of orders, then over the months scale, Jan, Feb, March and April witnessed the highest numbers of orders compared to the other months especially the plunge in the number of orders in May and June. Additionally, most of the weekdays have similarly high number of orders made compared to Tuesday and Wednesday where they have very few. Orders and Products overview “different timescales”
- 6. Year Month 2010 2011 2012 January 0 33 55 February 0 29 54 March 0 30 73 April 1 31 74 May 0 32 14 June 0 30 0 July 22 33 0 August 25 33 0 September 23 36 0 October 26 38 0 November 24 34 0 December 31 46 0 Due to the low amount of sales for both 2010 and 2012, we had to dig deeper to make sure if there is missing data or these years already have a low amount of sales. It turns out that there is missing data in the first half of 2010 and the second half of 2012. In addition, comparing the sales of each month over the years, we have found out that most of 2012 months have higher sales compared to 2011's and 2011 months have higher sales than 2010's.ئ Orders and Products overview
- 7. The first chart demonstrates the number of orders made and products sold across each country and it turns out that USA, Germany, Brazil and France have the highest numbers compared to the other countries which make them very good market. The corresponding revenue matches the same countries except in one case where Austria emerged with total sales larger than France despite its smaller number of orders. Orders and Products overview “Countries perspective”
- 8. On the other hand, the salespersons who made the highest amount of sales came Margaret in the first place with higher revenue and larger number of orders and products. While Janet who made a smaller number of orders than Nancy, sold more products and that's why Janet came second due to its total amount of sales. Orders and Products overview “Salesperson perspective”
- 9. The data clarified a positive correlation between the number of orders and number of products. So, we added the corresponding total sales to ensure if they are all matching together or not. Orders and Products correlation “Top 10 companies”
- 10. Top 10 Companies of Sold products and orders made and their corresponding sales Top 10 Companies of sales made Company Name Total Sold Products Total Orders Made Total Sales Company Name Total Sales Matching Criteria Total Sold Products Total Orders Made Save-a-lot Markets 116 31 104361.94 QUICK-Stop 110277.29 QUICK-Stop NA NA Ernst Handel 102 30 104874.97 Ernst Handel 104874.97 Ernst Handel NA NA QUICK-Stop 86 28 110277.29 Save-a-lot Markets 104361.94 Save-a-lot Markets NA NA Rattlesnake Canyon Grocery 71 18 51097.8 Rattlesnake Canyon Grocery 51097.8 Rattlesnake Canyon Grocery NA NA Hungry Owl All- Night Grocers 55 19 49979.9 Hungry Owl All- Night Grocers 49979.9 Hungry Owl All- Night Grocers NA NA Berglunds snabbköp 52 18 24927.58 Alfreds Futterkiste 44273 Not found 13 7 Frankenversand 48 15 26656.56 Hanari Carnes 32841.37 Not found 32 14 HILARIÓN- Abastos 45 18 22768.76 Königlich Essen 30908.38 Not found 39 14 Folk och fä HB 45 19 29567.56 Folk och fä HB 29567.56 Folk och fä HB NA NA Bon app' 44 17 21963.24 Mère Paillarde 28872.18 Not found 32 13 We figure out that it is 60% true as there are 4 out of 10 companies who made more revenue and a smaller number of products or orders. Therefore, the product price is a factor shall be considered regardless of the number of orders made, because the number of orders might not reflect a high revenue as expected. Orders and Products correlation “Top 10 companies”
- 11. Products Attribute Min (Cheapest Product) Konbu 4.8 Max (Most Expensive Product) Aniseed Syrup 40000 Average of Products' Prices 605.66 Median (Q2) 338.88 Mode 180 Q1 147 Q3 657 IQR 510 Range 39995.2 STDEV 1288.192461 Variance 1659439.817 In the above chart, we have a right-skewed distribution of the products' prices where the extreme values far from the peak on the high end more frequently than on the low. Besides, the mean "605" is greater than the median "339 and the mean overestimates the most common values. On the other hand, the standard deviation tells, on average, how far each score lies from the mean showed a high number "1288". Consequently, we moved to the IQR "510" which indicates how spread out the middle 50% of our set of data is. Products Prices Overview
- 12. The counting of top 10 sold products across countries Country Raclette Courdavault Camembert Pierrot Guaraná Fantástica Gorgonzola Telino Gnocchi di nonna Alice Tarte au sucre Jack's New England Clam Chowder Rhönbräu Klosterbier Chang Pavlova Venezuela 3 3 3 2 0 0 3 4 2 3 Germany 11 10 5 12 3 8 5 6 7 6 Brazil 3 7 6 6 4 1 5 4 4 2 Italy 2 1 3 1 1 1 2 0 1 0 France 2 0 3 3 3 6 6 6 2 6 Portugal 1 2 1 0 4 0 0 0 0 1 United States 8 7 5 8 16 16 7 9 9 10 Mexico 2 2 3 1 0 0 0 3 1 0 Canada 3 3 3 1 3 5 2 1 0 2 UK 3 4 2 4 3 2 3 0 3 1 Denmark 2 0 2 0 0 2 1 0 0 1 Argentina 1 0 0 1 0 0 1 1 0 1 Poland 0 1 1 1 0 1 0 1 2 0 Spain 0 2 2 0 1 1 0 1 1 0 Sweden 2 2 2 1 1 1 5 6 4 1 Austria 2 2 5 5 2 1 3 2 2 4 Ireland 3 1 0 2 1 1 2 1 2 1 Switzerland 1 2 1 1 3 2 1 1 3 1 Finland 2 1 1 1 2 0 0 0 0 2 Norway 1 0 2 0 0 0 1 0 0 1 Belgium 2 1 1 1 3 0 0 0 1 0 Total Counts 54 51 51 51 50 48 47 46 44 43 Total Sales 71155.7 46825.5 4504.4 14920.9 42593.1 47235.0 8680.3 8177.5 16356.0 17215.7 Average Price 1317.7 918.1 88.3 292.6 851.9 984.1 184.7 177.8 371.7 400.4 Mini Line Chart Then, we delve thoroughly to find out the top 10 sold products and it turns out that Raclette Courdavault, Camembert Pierrot and Guaraná Fantástica came in the first three places of 54, 51 and 51 respectively. However, the first two products have highest corresponding total sales and average price while the third one have very low corresponding total sales and average price. Therefore, as mentioned before the product price is a crucial factor to consider and so Gnocchi di nonna Alice and Tarte au sucre came in the third and fourth places of total sales and average price. On the other hand, the top 10 sold products are mainly in United States, Germany and Austria. Products Prices Overview “Top 10 sold products across countries”
- 13. The counting of the most promoted products over the years The average price of the most promoted products over the years Product Name 2010 2011 2012 2010 2011 2012 Raclette Courdavault 10 31 13 903.5 1154.0 2026.5 Camembert Pierrot 11 21 19 820.5 976.4 910.3 Guaraná Fantástica 11 19 21 50.6 85.8 110.4 Gorgonzola Telino 13 26 12 319.6 280.8 288.8 Gnocchi di nonna Alice 7 33 10 394.8 988.0 722.6 Tarte au sucre 11 22 15 873.1 983.6 1066.2 Jack's New England Clam Chowder 8 21 18 100.9 236.1 162.0 Rhönbräu Klosterbier 7 25 14 105.5 179.4 211.0 Chang 8 18 18 377.2 391.0 350.0 Pavlova 7 22 14 446.9 393.8 387.4 Moreover, we have checked how many products of each item had been sold over the years of 2010, 2011, and 2012 as mentioned in the above chart alongside how much the average price of each product changes over the same set of years. Products Prices Overview “Top 10 sold products over time”
- 14. The most promoting products average price change across the countries Country Raclette Courdavault Camembert Pierrot Guaraná Fantástica Gorgonzola Telino Gnocchi di nonna Alice Tarte au sucre Jack's New England Clam Chowder Rhönbräu Klosterbier Chang Pavlova Venezuela 2181.7 606.6 54.8 257.8 NA NA 254.8 210.8 611.8 417.0 Germany 1507.0 1160.9 67.0 213.2 699.2 1115.8 134.2 193.2 535.0 497.3 Brazil 1286.1 846.1 101.1 221.7 1073.5 394.4 65.1 183.4 201.2 432.6 Italy 386.7 136.0 62.3 180.0 361.0 443.7 173.7 NA 161.5 NA France 594.0 NA 53.4 355.6 690.3 1236.7 116.6 88.5 277.9 228.0 Portugal 396.0 300.9 36.0 NA 653.6 NA NA NA NA 593.3 United States 1524.2 740.6 77.3 317.7 760.4 1005.7 301.3 241.3 463.4 430.1 Mexico 591.3 238.0 49.5 250.0 NA NA NA 110.6 380.0 NA Canada 688.6 1532.8 75.0 399.0 1203.3 1154.7 154.0 77.5 NA 359.9 UK 256.7 1247.8 181.8 517.8 595.3 295.8 113.7 NA 190.0 739.5 Denmark 638.6 NA 101.3 NA NA 462.2 275.0 NA NA 232.1 Argentina 110.0 NA NA 12.5 NA NA 96.5 155.0 NA 104.7 Poland NA 510.0 54.0 300.0 NA 591.6 NA 232.5 190.0 NA Spain NA 323.0 37.8 NA 152.0 936.7 NA 310.0 380.0 NA Sweden 1292.5 544.0 31.7 18.8 2280.0 251.4 172.0 113.0 307.6 188.5 Austria 4257.0 2720.0 243.4 366.0 1786.0 3352.4 274.6 215.5 380.0 564.5 Ireland 1571.2 146.9 NA 400.0 1140.0 591.0 477.7 155.0 346.6 565.4 Switzerland 1320.0 936.7 45.9 375.0 889.2 473.3 55.0 368.1 307.2 486.5 Finland 859.4 693.6 90.0 375.0 788.5 NA NA NA NA 148.3 Norway 528.0 NA 45.0 NA NA NA 48.3 NA NA 261.8 Belgium 2420.0 1088.0 54.0 297.5 734.7 NA NA NA 380.0 NA Products Prices Overview “Top 10 sold products across countries”
- 15. Over and above, here's an illustration of the top 10 sold products' average prices changing across countries. It turns out that countries like Austria, the United States, Germany witnessed higher average prices compared to the other countries. Products Prices Overview “Top 10 sold products across countries”