Validated case study · Data Science

Humach Energy: Demand Forecasting

Use temporal structure, lag reasoning and legal forecasting validation to predict demand without peeking into the future.

Download mini_energy.csvUse Python, SQL, Excel or your preferred workflow unless a task specifies otherwise.
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Project dataset

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timestamptemperature_cdemand_mwrenewable_share_pct
2026-01-01 00:0012.8409.133.3
2026-01-01 01:0012.6398.229.0
2026-01-01 02:0012.8389.625.3
2026-01-01 03:0013.4384.022.4
2026-01-01 04:0014.4381.620.6
2026-01-01 05:0015.6382.620.0
2026-01-01 06:0017.0387.020.6
2026-01-01 07:0018.6394.522.4
2026-01-01 08:0020.2404.525.3
2026-01-01 09:0021.6416.429.0
2026-01-01 10:0022.8429.433.3
2026-01-01 11:0023.8442.538.0
2026-01-01 12:0024.4454.942.7
2026-01-01 13:0024.6465.847.0
2026-01-01 14:0024.4474.450.7
2026-01-01 15:0023.8480.053.6
2026-01-01 16:0022.8482.455.4
2026-01-01 17:0021.6481.456.0
2026-01-01 18:0020.2477.055.4
2026-01-01 19:0018.6469.553.6
2026-01-01 20:0017.0459.550.7
2026-01-01 21:0015.6447.647.0
2026-01-01 22:0014.4434.642.7
2026-01-01 23:0013.4421.538.0
2026-01-02 00:0013.4421.133.3
2026-01-02 01:0013.2410.229.0
2026-01-02 02:0013.4401.625.3
2026-01-02 03:0014.0396.022.4
2026-01-02 04:0015.0393.620.6
2026-01-02 05:0016.2394.620.0
2026-01-02 06:0017.6399.020.6
2026-01-02 07:0019.2406.522.4
2026-01-02 08:0020.8416.525.3
2026-01-02 09:0022.2428.429.0
2026-01-02 10:0023.4441.433.3
2026-01-02 11:0024.4454.538.0
2026-01-02 12:0025.0466.942.7
2026-01-02 13:0025.2477.847.0
2026-01-02 14:0025.0486.450.7
2026-01-02 15:0024.4492.053.6
2026-01-02 16:0023.4494.455.4
2026-01-02 17:0022.2493.456.0
2026-01-02 18:0020.8489.055.4
2026-01-02 19:0019.2481.553.6
2026-01-02 20:0017.6471.550.7
2026-01-02 21:0016.2459.647.0
2026-01-02 22:0015.0446.642.7
2026-01-02 23:0014.0433.538.0
48 rows4 columnsmini_energy.csv
Project workspace

Analyse → validate → submit.

Numeric and decision tasks are auto-checked. Written reasoning is checked for completeness and key ideas, then included in your local submission report.

0/5 validated
01

How many hourly observations are in the dataset?

02

What is the maximum demand (MW) in the dataset?

03

What is average renewable share (%)?

04

Which split is safest for a forecast?

05

Name one lagged or rolling feature you would create and explain why.

Submit your project locally

HumachLearn stores no server-side data. Submission creates a portable JSON report containing your answers, validation state and timestamp.