Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
csv
Languages:
Arabic
Size:
10K - 100K
License:
metadata
license: apache-2.0
task_categories:
- text-classification
language:
- ar
tags:
- news
- arabic
- classification
pretty_name: news_2026_exercise
size_categories:
- 10K<n<100K
news_2026_exercise
Arabic news dataset for text classification.
| Column | Description |
|---|---|
title |
News title |
content |
News body |
category |
Label: سياسة, اقتصاد, صحة, رياضة |
28,000 rows (7,000 per category).
Download and load as pandas
from datasets import load_dataset
import pandas as pd
ds = load_dataset("maher13/news_2026_exercise")
df = ds["train"].to_pandas()
print(df.head())
Sample N rows from each category
from datasets import load_dataset
import pandas as pd
N = 100 # change this
ds = load_dataset("maher13/news_2026_exercise")
df = ds["train"].to_pandas()
sample_df = (
df.groupby("category", group_keys=False)
.apply(lambda x: x.sample(n=min(N, len(x)), random_state=42))
.reset_index(drop=True)
)
print(sample_df["category"].value_counts())
print(sample_df.head())