European legislation from CELLAR/EUROVOC, English entries only of https://huggingface.co/datasets/EuropeanParliament/Eurovoc. This data is enriched with embeddings, ready for semantic search. Last update 16.05.2024: 352011 entries.

  Usage





  With Pandas / Polars

Simply download the parquet file and read with pandas or polars. import pandas as pd # or import polars as pd df = pd.read_parquet("CELLAR_EN_16_05_2024.parquet") df

  With HF datsets

from datasets import… See the full description on the dataset page: https://huggingface.co/datasets/do-me/Eurovoc_en.

Solar activity- and height-adjusted plasma density measurements in the polar cap (i.e., above 80° latitude in Modified Apex₁₁₀ coordinates) from the Swarm and CHAMP satellites. covering the entire CHAMP mission period (2002–2009) and the Swarm mission period from launch through February 2020.

Plasma density measurements are scaled to a nominal solar activity level of <F10.7>₂₇ = 80 sfu, and an altitude of 500 km, as described in Hatch et al. (submitted to JGR: Space Physics; ESSOAr pre-print)

This dataset was prepared as a part of the "Swarm+ Coupling High-Low Atmosphere Interactions: Ion Outflow" project (project website) (ESA website), and is funded by European Space Agency Contract #4000126731.

Data are stored in HDF5 format as a Python Pandas dataframe. They can be loaded into Python via the following.

import pandas as pd

df = pd.read_hdf('CHAMP_Swarm_polarcap_adjDensity.hdf',key='df')

The data columns are

• 'NeAdj' : Solar activity- and height-adjusted plasma density (cm^-3)
• 'a110lat' : Modified Apex₁₁₀ latitude (deg)
• 'a110lon' : Modified Apex₁₁₀ longitude (deg)
• 'mlt' : Modified Apex₁₁₀ magnetic local time
• 'h_km' : satellite altitude (km)
• 'gclat' : geocentric latitude (deg)
• 'gclon' : geocentric longitude (deg)
• 'sat' : satellite identifier (string, one of 'A', 'B',' 'C', or 'CHAMP')

This data is downloaded from the link shared in the PlaygroundS4E06 episode on the data page. We add a column id to keep consistency with the competition data and upload herewith.
Please feel free to use this dataset as part of your pipeline.

Key links:- 1. Competition - https://www.kaggle.com/competitions/playground-series-s4e6 2. Data page- https://www.kaggle.com/competitions/playground-series-s4e6/data
3. Original dataset link- https://archive.ics.uci.edu/dataset/697/predict+students+dropout+and+academic+success

This is a .csv file. Please use pandas.read_csv() or polars.scan_csv() to read in the file

Best regards!

ClinVar variants

For more information check out our paper and repository.

  Usage

Pandas

import pandas as pd df = pd.read_parquet("hf://datasets/songlab/clinvar/test.parquet")

Polars

import polars as pl df = pl.read_parquet("https://huggingface.co/datasets/songlab/clinvar/resolve/main/test.parquet")

Datasets

from datasets import load_dataset dataset = load_dataset("songlab/clinvar", split="test")

COSMIC variants

For more information check out our paper and repository.

  Usage

Pandas

import pandas as pd df = pd.read_parquet("hf://datasets/songlab/cosmic/test.parquet")

Polars

import polars as pl df = pl.read_parquet("https://huggingface.co/datasets/songlab/cosmic/resolve/main/test.parquet")

Datasets

from datasets import load_dataset dataset = load_dataset("songlab/cosmic", split="test")