item_id large_stringlengths 11 15 | store_id large_stringclasses 10
values | date timestamp[ns]date 2016-04-25 00:00:00 2016-05-22 00:00:00 | forecast float32 0 158 | actual int64 0 196 | lower_ci_95 float32 0 26.7 | upper_ci_95 float32 0 244 | model_name large_stringclasses 1
value |
|---|---|---|---|---|---|---|---|
HOBBIES_1_254 | WI_2 | 2016-04-25T00:00:00 | 1.686968 | 3 | 0 | 7.657314 | XGBoost |
HOBBIES_2_024 | WI_2 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOUSEHOLD_2_394 | CA_3 | 2016-04-25T00:00:00 | 0.403876 | 1 | 0 | 2.379834 | XGBoost |
HOBBIES_1_374 | CA_4 | 2016-04-25T00:00:00 | 0.494939 | 1 | 0 | 2.652119 | XGBoost |
HOUSEHOLD_2_159 | TX_1 | 2016-04-25T00:00:00 | 0.921502 | 0 | 0 | 3.654452 | XGBoost |
FOODS_1_053 | WI_2 | 2016-04-25T00:00:00 | 0.344652 | 0 | 0 | 1.987319 | XGBoost |
HOUSEHOLD_2_212 | WI_3 | 2016-04-25T00:00:00 | 0.924993 | 2 | 0 | 3.863131 | XGBoost |
HOBBIES_1_189 | TX_1 | 2016-04-25T00:00:00 | 2.425884 | 2 | 0 | 8.601544 | XGBoost |
FOODS_2_009 | CA_2 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOUSEHOLD_2_483 | CA_1 | 2016-04-25T00:00:00 | 1.776977 | 4 | 0 | 4.978715 | XGBoost |
HOBBIES_1_055 | TX_3 | 2016-04-25T00:00:00 | 0.351232 | 0 | 0 | 2.225812 | XGBoost |
FOODS_3_438 | TX_2 | 2016-04-25T00:00:00 | 2.209049 | 0 | 0 | 7.168899 | XGBoost |
FOODS_1_028 | CA_2 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_3_432 | WI_2 | 2016-04-25T00:00:00 | 1.922931 | 1 | 0 | 5.05863 | XGBoost |
HOUSEHOLD_2_375 | WI_3 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOUSEHOLD_2_420 | TX_3 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_1_023 | WI_3 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOUSEHOLD_1_213 | TX_1 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_2_302 | TX_1 | 2016-04-25T00:00:00 | 1.054531 | 1 | 0 | 3.865001 | XGBoost |
HOUSEHOLD_1_127 | TX_1 | 2016-04-25T00:00:00 | 1.667053 | 1 | 0 | 5.040258 | XGBoost |
HOUSEHOLD_2_177 | TX_3 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOBBIES_1_361 | CA_3 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOBBIES_1_347 | CA_3 | 2016-04-25T00:00:00 | 0.59012 | 1 | 0 | 2.634583 | XGBoost |
HOUSEHOLD_1_538 | CA_3 | 2016-04-25T00:00:00 | 1.525171 | 2 | 0 | 5.018558 | XGBoost |
HOUSEHOLD_1_173 | TX_2 | 2016-04-25T00:00:00 | 2.087132 | 6 | 0 | 6.790286 | XGBoost |
HOBBIES_2_115 | TX_3 | 2016-04-25T00:00:00 | 0.705266 | 0 | 0 | 3.56635 | XGBoost |
HOUSEHOLD_2_440 | CA_2 | 2016-04-25T00:00:00 | 0.140673 | 0 | 0 | 1.528345 | XGBoost |
FOODS_1_001 | WI_3 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_3_585 | CA_3 | 2016-04-25T00:00:00 | 1.410873 | 4 | 0 | 4.266878 | XGBoost |
HOUSEHOLD_2_432 | TX_2 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOBBIES_1_040 | CA_4 | 2016-04-25T00:00:00 | 1.302469 | 1 | 0 | 3.947655 | XGBoost |
HOUSEHOLD_1_153 | CA_4 | 2016-04-25T00:00:00 | 0.897622 | 0 | 0 | 3.627856 | XGBoost |
HOUSEHOLD_2_490 | TX_1 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_1_057 | WI_2 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_3_711 | TX_3 | 2016-04-25T00:00:00 | 5.787514 | 15 | 0 | 28.569771 | XGBoost |
HOUSEHOLD_1_292 | CA_3 | 2016-04-25T00:00:00 | 2.029737 | 0 | 0 | 5.176387 | XGBoost |
FOODS_2_235 | CA_3 | 2016-04-25T00:00:00 | 0.898903 | 1 | 0 | 3.805348 | XGBoost |
FOODS_1_090 | TX_1 | 2016-04-25T00:00:00 | 0.438263 | 1 | 0 | 2.786457 | XGBoost |
FOODS_2_362 | TX_2 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_2_245 | TX_1 | 2016-04-25T00:00:00 | 1.450529 | 2 | 0 | 4.206569 | XGBoost |
HOBBIES_1_156 | WI_2 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_2_369 | CA_3 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_3_048 | TX_3 | 2016-04-25T00:00:00 | 1.092893 | 2 | 0 | 4.096552 | XGBoost |
HOBBIES_1_158 | WI_1 | 2016-04-25T00:00:00 | 1.861221 | 0 | 0 | 4.226944 | XGBoost |
FOODS_3_543 | CA_2 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOBBIES_1_269 | CA_4 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOUSEHOLD_1_242 | TX_3 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOBBIES_1_037 | CA_4 | 2016-04-25T00:00:00 | 0.417061 | 1 | 0 | 1.95656 | XGBoost |
HOUSEHOLD_1_238 | TX_3 | 2016-04-25T00:00:00 | 1.313721 | 2 | 0 | 3.981656 | XGBoost |
FOODS_2_306 | WI_3 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOUSEHOLD_2_412 | CA_2 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOBBIES_1_026 | CA_4 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOUSEHOLD_2_308 | WI_2 | 2016-04-25T00:00:00 | 0.366767 | 1 | 0 | 1.948372 | XGBoost |
HOBBIES_1_220 | WI_3 | 2016-04-25T00:00:00 | 0.3958 | 0 | 0 | 2.273846 | XGBoost |
FOODS_2_215 | CA_2 | 2016-04-25T00:00:00 | 0.000468 | 0 | 0 | 0.000468 | XGBoost |
HOUSEHOLD_2_153 | TX_3 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_2_195 | WI_1 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOUSEHOLD_1_528 | CA_3 | 2016-04-25T00:00:00 | 0.918136 | 0 | 0 | 3.715485 | XGBoost |
FOODS_3_790 | CA_2 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOUSEHOLD_1_395 | WI_3 | 2016-04-25T00:00:00 | 0.306351 | 0 | 0 | 1.989661 | XGBoost |
HOBBIES_1_098 | WI_2 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_2_328 | TX_2 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_2_371 | CA_1 | 2016-04-25T00:00:00 | 7.309457 | 5 | 0.764208 | 14.658998 | XGBoost |
HOUSEHOLD_2_466 | TX_3 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOUSEHOLD_1_153 | WI_1 | 2016-04-25T00:00:00 | 1.552684 | 2 | 0 | 5.567164 | XGBoost |
FOODS_2_025 | CA_1 | 2016-04-25T00:00:00 | 0.689611 | 1 | 0 | 3.100186 | XGBoost |
HOUSEHOLD_2_173 | CA_1 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_2_234 | TX_2 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_2_171 | CA_1 | 2016-04-25T00:00:00 | 0.536042 | 1 | 0 | 2.730844 | XGBoost |
HOUSEHOLD_2_513 | WI_1 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOUSEHOLD_2_460 | WI_1 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOBBIES_1_131 | WI_1 | 2016-04-25T00:00:00 | 1.701951 | 0 | 0 | 5.21764 | XGBoost |
HOBBIES_1_076 | CA_3 | 2016-04-25T00:00:00 | 1.727152 | 0 | 0 | 4.216565 | XGBoost |
FOODS_2_230 | WI_3 | 2016-04-25T00:00:00 | 0.030872 | 0 | 0 | 1.156099 | XGBoost |
FOODS_1_088 | CA_1 | 2016-04-25T00:00:00 | 0.894723 | 1 | 0 | 4.513608 | XGBoost |
FOODS_3_342 | CA_2 | 2016-04-25T00:00:00 | 4.932938 | 5 | 0.032162 | 12.16759 | XGBoost |
HOUSEHOLD_1_028 | WI_3 | 2016-04-25T00:00:00 | 1.29412 | 0 | 0 | 5.176962 | XGBoost |
FOODS_2_134 | CA_1 | 2016-04-25T00:00:00 | 1.440952 | 0 | 0 | 4.51479 | XGBoost |
FOODS_3_316 | WI_3 | 2016-04-25T00:00:00 | 0.460262 | 0 | 0 | 2.502951 | XGBoost |
HOBBIES_1_140 | WI_3 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOUSEHOLD_2_091 | TX_1 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOBBIES_1_087 | WI_1 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOBBIES_1_072 | WI_3 | 2016-04-25T00:00:00 | 0.580103 | 2 | 0 | 3.026852 | XGBoost |
FOODS_2_017 | TX_2 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_3_518 | CA_3 | 2016-04-25T00:00:00 | 0.69351 | 0 | 0 | 3.718653 | XGBoost |
HOBBIES_1_122 | TX_2 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_1_097 | CA_3 | 2016-04-25T00:00:00 | 1.29155 | 4 | 0 | 4.106828 | XGBoost |
FOODS_3_128 | TX_2 | 2016-04-25T00:00:00 | 0.133605 | 0 | 0 | 1.554244 | XGBoost |
FOODS_3_216 | CA_3 | 2016-04-25T00:00:00 | 0.54162 | 2 | 0 | 2.875539 | XGBoost |
FOODS_3_359 | CA_1 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_3_441 | CA_3 | 2016-04-25T00:00:00 | 0.026043 | 0 | 0 | 0.183802 | XGBoost |
HOUSEHOLD_2_066 | CA_4 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOBBIES_1_416 | TX_2 | 2016-04-25T00:00:00 | 1.755543 | 2 | 0 | 5.447857 | XGBoost |
HOBBIES_1_292 | WI_1 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOUSEHOLD_2_273 | WI_1 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
HOUSEHOLD_1_487 | CA_1 | 2016-04-25T00:00:00 | 1.576403 | 3 | 0 | 4.910198 | XGBoost |
FOODS_2_056 | WI_3 | 2016-04-25T00:00:00 | 3.24144 | 4 | 0 | 7.832208 | XGBoost |
HOUSEHOLD_2_382 | WI_3 | 2016-04-25T00:00:00 | 0 | 0 | 0 | 0.000242 | XGBoost |
FOODS_3_688 | CA_4 | 2016-04-25T00:00:00 | 1.196251 | 0 | 0 | 4.666256 | XGBoost |
FOODS_3_467 | CA_4 | 2016-04-25T00:00:00 | 0.547117 | 0 | 0 | 2.942971 | XGBoost |
End of preview. Expand in Data Studio
M5 Retail Demand Forecasting & Inventory Risk Benchmarks
This dataset contains the heavily processed artifacts, extracted time-series features, baseline benchmarks, and model artifacts for the M5 Retail Demand Forecasting dataset.
It includes:
- Over 1GB of highly engineered temporal, pricing, and calendar features.
- Volatility and shortfall risk metrics for 42,840 time series.
- XGBoost, Prophet, and SARIMA predictions (point + 95% intervals).
- Isolation Forest anomaly detection outputs.
Credits
This dataset is prepared as an independent extension of the GitHub Repo: https://github.com/rudraakshreddy/demand-sentinel
Prepared by:
- github: @rudraakshreddy (Yeddula Rudraaksh Reddy)
- github: @snchakri (Shiva Naga Chakri M.)
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