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Level: Intermediate
Recommended Use: Regression Models
Domain: Business

Daily Demand Forecasting Orders Data Set

Predict total number of demand of orders


This intermediate level data set has 60 rows and 13 columns. 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.

This data set is recommended for learning and practicing your skills in exploratory data analysis, data visualization, and regression modelling techniques. It also allows you to practice with large number of features. Feel free to explore the data set with multiple supervised and unsupervised learning techniques. The Following data dictionary gives more details on this data set:


Data Dictionary

Column Position Atrribute Name Definition Data Type Example % Null Ratios
1 Week of the month Week of the month (1: first, 2: second, 3: third, 4: fourth, 5:fifth) Quantitative 1, 2, 3 0
2 Day of the week Day of the week (2: Monday, 3: Tuesday, 4: Wednesday, 5:Thursday, 6:Friday) Quantitative 2, 3, 4 0
3 Non-urgent order Non-urgent order Quantitative 171.297, 220.343, 127.805 0
4 Urgent order Urgent order Quantitative 127.667, 141.406, 114.813 0
5 Order type A Order type A Quantitative 41.542, 46.241, 39.025 0
6 Order type B Order type B Quantitative 113.294, 120.865, 110.74 0
7 Order type C Order type C Quantitative 162.284, 196.296, 94.47 0
8 Fiscal sector orders Fiscal sector orders Quantitative 18.156, 1.653, 1.617 0
9 Orders from the traffic controller sector Orders from the traffic controller sector Quantitative 49971, 34878, 33366
10 Banking orders (1) Banking orders (1) Quantitative 33703, 32905, 21103 0
11 Banking orders (2) Banking orders (2) Quantitative 69054, 117137, 84558 0
12 Banking orders (3) Banking orders (3) Quantitative 18423, 29188, 16683 0
13 Target (Total orders) Target (Total orders) Quantitative 317.12, 363.402, 244.235 0

Acknowledgement

This data set has been sourced from the Machine Learning Repository of University of California, Irvine Daily Demand Forecasting Orders Data Set (UC Irvine). The UCI page mentions the following publication as the original source of the data set:

Ferreira, R. P., Martiniano, A., Ferreira, A., Ferreira, A., & Sassi, R. J. (2016). Study on daily demand forecasting orders using artificial neural network. IEEE Latin America Transactions, 14(3), 1519-1525