README.md

metadata

dataset_info:
  features:
    - name: Event_ID
      dtype: text
    - name: Timestamp
      dtype: timestamp
    - name: Vehicle_Type
      dtype: text
    - name: Speed_kmh
      dtype: text
    - name: Latitude
      dtype: text
    - name: Longitude
      dtype: text
    - name: Event_Type
      dtype: text
    - name: Severity
      dtype: text
  splits:
    - name: default
      num_bytes: 3031KB
      num_examples: 30000

Flowmatic Cleaned Dataset

Overview

This dataset was cleaned and exported by Flowmatic, an intelligent data preparation platform.

Pipeline Run ID: cmnr643le000ml1do503vfdbn Generated: 2026-04-09T08:14:00.156Z

Dataset Statistics

• Total Records: 30 000
• Total Columns: 8
• File: cleaned_data.csv

Column Information

Column	Type	Non-Null	Null	Sample Values
Event_ID	text	30000	0	" 1", " 2", " 3"
Timestamp	timestamp	30000	0	" 2024-02-01 08:00:00", " 2024-02-01 08:00:00", " 2024-02-01 08:00:00"
Vehicle_Type	text	30000	0	" Bus ", " Truck ", " Truck "
Speed_kmh	text	30000	0	" 61", " 74", " 84"
Latitude	text	30000	0	" 51.130119", " 51.130046", " 51.129601"
Longitude	text	30000	0	" 71.43348 ", " 71.434301", " 71.432699"
Event_Type	text	30000	0	" Normal ", " Normal ", " Normal "
Severity	text	30000	0	" Low", " Low", " Low"

Data Quality

This dataset has been processed through Flowmatic's cleaning pipeline:

• ✅ Duplicates removed
• ✅ Missing values handled (interpolation/forward-fill)
• ✅ Outliers processed (winsorization)
• ✅ Type consistency validated
• ✅ Records exported

Usage

Load the dataset using Hugging Face datasets library:

from datasets import load_dataset

dataset = load_dataset('pushthetempo/test')
df = dataset['train'].to_pandas()

Or load directly as CSV:

import pandas as pd

df = pd.read_csv('https://huggingface.co/datasets/pushthetempo/test/raw/main/cleaned_data.csv')

License

This dataset is released under the CC BY 4.0 license.

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Processed with Flowmatic