Daily Demand Forecasting Orders
Donated on 11/20/2017
The dataset was collected during 60 days, this is a real database of a brazilian logistics company.
Dataset Characteristics
Time-Series
Subject Area
Business
Associated Tasks
Regression
Feature Type
Integer
# Instances
60
# Features
-
Dataset Information
Additional Information
The database was collected during 60 days, this is a real database of a Brazilian company of large logistics. Twelve predictive attributes and a target that is the total of orders for daily. treatment
Has Missing Values?
No
Variables Table
| Variable Name | Role | Type | Demographic | Description | Units | Missing Values |
|---|---|---|---|---|---|---|
| no | ||||||
| no | ||||||
| no | ||||||
| no | ||||||
| no | ||||||
| no | ||||||
| no | ||||||
| no | ||||||
| no | ||||||
| no |
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Additional Variable Information
The dataset was collected during 60 days, this is a real database of a brazilian logistics company. The dataset has twelve predictive attributes and a target that is the total of orders for daily treatment. The database was used in academic research at the Universidade Nove de Julho. .arff header for Weka: @relation Daily_Demand_Forecasting_Orders @attribute Week_of_the_month {1.0, 2.0, 3.0, 4.0, 5.0} @attribute Day_of_the_week_(Monday_to_Friday) {2.0, 3.0, 4.0, 5.0, 6.0} @attribute Non_urgent_order integer @attribute Urgent_order integer @attribute Order_type_A integer @attribute Order_type_B integer @attribute Order_type_C integer @attribute Fiscal_sector_orders integer @attribute Orders_from_the_traffic_controller_sector integer @attribute Banking_orders_(1) integer @attribute Banking_orders_(2) integer @attribute Banking_orders_(3) integer @attribute Target_(Total_orders) integer @data
Ferreira,Ricardo, Martiniano,Andrea, Ferreira,Arthur, Ferreira,Aleister, and Sassi,Renato. (2017). Daily Demand Forecasting Orders. UCI Machine Learning Repository. https://doi.org/10.24432/C5BC8T.
@misc{misc_daily_demand_forecasting_orders_409,
author = {Ferreira,Ricardo, Martiniano,Andrea, Ferreira,Arthur, Ferreira,Aleister, and Sassi,Renato},
title = {{Daily Demand Forecasting Orders}},
year = {2017},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: https://doi.org/10.24432/C5BC8T}
}pip install ucimlrepo
from ucimlrepo import fetch_ucirepo # fetch dataset daily_demand_forecasting_orders = fetch_ucirepo(id=409) # data (as pandas dataframes) X = daily_demand_forecasting_orders.data.features y = daily_demand_forecasting_orders.data.targets # metadata print(daily_demand_forecasting_orders.metadata) # variable information print(daily_demand_forecasting_orders.variables)
Creators
Ricardo Ferreira
Andrea Martiniano
Arthur Ferreira
Aleister Ferreira
Renato Sassi
DOI
License
This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.
This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.