Dataset Card for "traffic_hourly"

More Information needed

Download the Dataset:

from datasets import load_dataset

dataset = load_dataset("LeoTungAnh/traffic_hourly")

Dataset Card for Electricity Consumption

this dataset encompasses 862 hourly time series data points revealing the road occupancy rates across freeways in the San Francisco Bay area from 2015 to 2016.

Preprocessing information:

• Grouped by hour (frequency: "1H").
• Applied Standardization as preprocessing technique ("Std").

Dataset information:

• Number of time series: 862
• Number of training samples: 17448
• Number of validation samples: 17496 (number_of_training_samples + 48)
• Number of testing samples: 17544 (number_of_validation_samples + 48)

Dataset format:

  Dataset({
  
      features: ['start', 'target', 'feat_static_cat', 'feat_dynamic_real', 'item_id'],
      
      num_rows: 862
      
  })

Data format for a sample:

• 'start': datetime.datetime

• 'target': list of a time series data

• 'feat_static_cat': time series index

• 'feat_dynamic_real': None

• 'item_id': name of time series

Data example:

{'start': datetime.datetime(2015, 1, 1, 0, 0, 1),
 'feat_static_cat': [0],
 'feat_dynamic_real': None,
 'item_id': 'T1',
 'target': [-0.7127609544951682, -0.6743409178438863, -0.3749847989359815, ... 0.12447567753068307,...]
}

Usage:

• The dataset can be used by available Transformer, Autoformer, Informer of Huggingface.
• Other algorithms can extract data directly by making use of 'target' feature.