About:
This dataset contains data on a variety of sales channels, including Shiprocket and INCREFF, as well as financial information on related expenses and profits.
Data Source: [Kaggle](https://www.kaggle.com/datasets/thedevastator/unlock-profits-with-e-commerce-sales-data)
In addition to this, there are MRPs across multiple stores like Ajio MRP, Amazon MRP, Amazon FBA MRP, Flipkart MRP, Limeroad MRP, Myntra MRP, and Paytm MRP.
Also, there are transactional parameters like Date of sale, months, category, fulfilled by B2B, Status, Qty, Currency, and Gross amt.
Data Contains below columns and data-types:
vars n mean sd median trimmed mad min max range skew
Category* 1 1330 2.46 0.78 2.0 2.32 0.00 1 5 4 1.40
Amazon.FBA.MRP* 2 1330 16.91 12.29 15.0 14.99 11.86 1 53 52 1.21
Amazon.MRP* 3 1330 16.91 12.29 15.0 14.99 11.86 1 53 52 1.21
Myntra.MRP* 4 1330 17.03 11.28 15.0 15.50 11.86 1 51 50 1.11
Ajio.MRP* 5 1330 16.56 12.01 13.5 14.68 11.12 1 52 51 1.22
Flipkart.MRP* 6 1330 16.62 11.97 14.0 14.75 11.86 1 52 51 1.21
Limeroad.MRP* 7 1330 16.61 11.91 13.5 14.74 9.64 1 52 51 1.24
Paytm.MRP* 8 1330 16.52 11.95 13.5 14.62 10.38 1 52 51 1.24
Snapdeal.MRP* 9 1330 16.56 11.93 13.5 14.68 11.12 1 52 51 1.24
kurtosis se
Category* 2.07 0.02
Amazon.FBA.MRP* 0.87 0.34
Amazon.MRP* 0.87 0.34
Myntra.MRP* 0.77 0.31
Ajio.MRP* 0.90 0.33
Flipkart.MRP* 0.92 0.33
Limeroad.MRP* 0.99 0.33
Paytm.MRP* 0.99 0.33
Snapdeal.MRP* 0.99 0.33
Welch Two Sample t-test
data: df$Amazon.MRP and df$Flipkart.MRP
t = 0.16743, df = 2440, p-value = 0.867
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-48.53192 57.59335
sample estimates:
mean of x mean of y
2237.185 2232.654
Pearson's Chi-squared test
data: df$Amazon.MRP and df$Myntra.MRP
X-squared = 35869, df = 1190, p-value < 2.2e-16