Datasets:
|
Download README.md from THULab/click_target_preprocess_test_three_camera: direct link, hf CLI and curl.
- Browser
- Download file 1.7 kB
-
https://huggingface.co/datasets/THULab/click_target_preprocess_test_three_camera/resolve/main/README.md
- Command line
-
hf download hf://datasets/THULab/click_target_preprocess_test_three_camera/README.md
-
curl -L -o README.md https://huggingface.co/datasets/THULab/click_target_preprocess_test_three_camera/resolve/main/README.md
1.7 kB
metadata
license: apache-2.0
task_categories:
- time-series-forecasting
tags:
- tsfile
- timeseries
- time-series
- format:tsfile
pretty_name: click_target_preprocess_test_three_camera
configs:
- config_name: default
data_files:
- split: train
path: data/click_target_preprocess_test_three_camera.tsfile
click_target_preprocess_test_three_camera (TsFile)
Apache TsFile version of Greynar/ClickTargetPreprocessTestThreeCamera.
- Converted rows: 37,577
- Data files:
['data/click_target_preprocess_test_three_camera.tsfile']
Usage
Install the Apache TsFile Python SDK (pip install tsfile) and read a converted file:
from pathlib import Path
from tsfile import TsFileReader
path = Path("data/click_target_preprocess_test_three_camera.tsfile")
with TsFileReader(str(path)) as reader:
schemas = reader.get_all_table_schemas()
print("tables:", list(schemas))
table_name = next(iter(schemas))
table = schemas[table_name]
columns = [column.get_column_name() for column in table.get_columns()]
print("columns:", columns)
field_names = [
column.get_column_name()
for column in table.get_columns()
if column.get_column_name() not in {"Time", "time"}
]
if field_names:
with reader.query_table(table_name, field_names[:3], batch_size=1024) as result:
batch = result.read_arrow_batch()
if batch is not None:
print(batch.to_pandas().head())
Source & license
- Original dataset: https://huggingface.co/datasets/Greynar/ClickTargetPreprocessTestThreeCamera
- License: apache-2.0