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Update README.md

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@@ -6368,14 +6368,14 @@ All datasets formatting follows a similar structure.
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  ### Data Fields
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  The data fields are the same among all datasets and splits.
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- The datetime column is left out when no data is available.
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- - `datetime`: a `timestamp[ns]` sequence, containing event datetime if available.
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  - `type_event`: a classification label (`int64`) sequence.
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  - `time_since_last_event`: a `float64` sequence of inter-event times.
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  - `time_since_start`: a `float64` sequence of event timestamps since sequence start.
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  - `seq_idx`: an `int64` feature uniquely identifying sequences in the split.
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  - `dim_process`: an `int64` feature representing total number of classes in the dataset.
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  - `seq_len`: an `int64` feature containing sequence length.
 
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  The classification labels differ for each dataset.
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  The corresponding labels for each event type can be read from metadata like this
 
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  ### Data Fields
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  The data fields are the same among all datasets and splits.
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+ The datetime column is optional and left out when no data is available.
 
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  - `type_event`: a classification label (`int64`) sequence.
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  - `time_since_last_event`: a `float64` sequence of inter-event times.
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  - `time_since_start`: a `float64` sequence of event timestamps since sequence start.
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  - `seq_idx`: an `int64` feature uniquely identifying sequences in the split.
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  - `dim_process`: an `int64` feature representing total number of classes in the dataset.
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  - `seq_len`: an `int64` feature containing sequence length.
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+ - `datetime`: (optional) a `timestamp[ns]` sequence, containing event datetime if available.
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  The classification labels differ for each dataset.
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  The corresponding labels for each event type can be read from metadata like this