About the Data

This dataset contains pricing information of electronic products. There are 25 columns including the target variable. Some of the variables are listed below:

prices.availability: if the product is available at the given price
prices.condition: condition of the product
prices.currency: price currency
prices.isSale: Is the product on sale at given price
prices.merchant: The merchant
imageURLs: product image url
manufacturer: Manufacturer of the product
manufacturerNumber: Manufacturer number
name: Name of the product
primaryCategories: Primary category of the product
weight: weight of the product

To load the training data in your jupyter notebook, use the below command:

import pandas as pd

ep_data = pd.read_csv("https://raw.githubusercontent.com/dphi-official/Datasets/master/electronic_product/electronic_product/Training_set_label.csv" )

Saving Prediction File & Sample Submission

You can find more details on how to save a prediction file here: https://discuss.dphi.tech/t/how-to-submit-predictions/548

Sample submission: You should submit a CSV file with a header row and the sample submission can be found below

prediction

164.9

761.3

174.7

594.8

144.4

1760

.

.

Etc.

Note that the header name should be prediction else it will throw an evaluation error. A sample submission file can be found here

Test Dataset

Load the test data (name it as test_data). You can load the data using the below command.

test_data = pd.read_csv('https://raw.githubusercontent.com/dphi-official/Datasets/master/electronic_product/electronic_product/Testing_set_label.csv')

Here the target column is deliberately not there as you need to predict it

Acknowledgement

This data is downloaded from data.world.

Data Sprint #16: Electronic Products Pricing

Challenge Starts

Registration Ends

Challenge Ends