Dataset Viewer
Auto-converted to Parquet Duplicate
batch_id
int64
4
7
table_id
int64
900
2.1k
reconstruction_id
int64
6.1k
7.9k
graph_data
stringclasses
3 values
column_names
stringclasses
3 values
num_nodes
int64
13
105
num_edges
int64
110
10.9k
serialization
stringclasses
1 value
original_size
int64
8.08k
40k
serialized_size
int64
1.44k
57.9k
key
stringclasses
3 values
4
2,100
6,100
{"num_nodes": 53, "node_types": [0.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0], "weights": [-0.153440...
Numéro d'enregistrement,Ajouter ou enlever l'objet de la sélection_comp0,Ajouter ou enlever l'objet de la sélection_comp1,Ajouter ou enlever l'objet de la sélection_comp2,Ajouter ou enlever l'objet de la sélection_comp3,Ajouter ou enlever l'objet de la sélection_comp4,Ajouter ou enlever l'objet de la sélection_comp5,Aj...
53
2,756
dense
27,346
24,010
tables/job=commoncrawl_000003/batch=000148/sWVdZ7OUh6J5VdbS_3F3CqmXD85ZZl5Vz2VBixZzVWQ=
6
1,800
7,800
{"num_nodes": 13, "node_types": [0.0, 0.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 4.0, 3.0], "weights": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, -0.04824506491422653, -0.027681827545166016, -0.08517519384622574, -0.027681827545166016, -0.0...
Unnamed: 0,Свойство,Определено_DisplayObject,Определено_DisplayObjectContainer,Определено_Form,Определено_InteractiveObject,Определено_Object,Определено_SkinnableComponent,Определено_SkinnableContainer,Определено_SkinnableContainerBase,Определено_Sprite,Определено_UIComponent,Свойство.1_comp0
13
110
dense
39,962
1,443
tables/job=commoncrawl_000003/batch=000452/aScUv1mAGXYo3M89LABl3RAyrTCHabeXJQAQ15nRWbk=
7
900
7,900
{"num_nodes": 105, "node_types": [3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 3.0, 0.0, 4.0, 0.0, 0.0, 4.0, 3.0, 3.0, 3...
Артикул_comp0,Артикул_comp1,Артикул_comp2,Артикул_comp3,Артикул_comp4,Артикул_comp5,Артикул_comp6,Артикул_comp7,Артикул_comp8,Артикул_comp9,Артикул_comp10,Артикул_comp11,Артикул_comp12,Артикул_comp13,Артикул_comp14,Артикул_comp15,Артикул_comp16,Артикул_comp17,Артикул_comp18,Артикул_comp19,Артикул_comp20,Артикул_comp21,...
105
10,920
dense
8,082
57,886
tables/job=commoncrawl_000003/batch=000452/xkxKShw2WxKyn9xM1bkoEXQ-Z53lCy5ngYKwbiqt3yI=

YAML Metadata Warning:The task_categories "tabular-to-graph" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

YAML Metadata Warning:The task_categories "graph-learning" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

YAML Metadata Warning:The task_categories "network-analysis" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

GraphTab Sample Dataset

This dataset contains tables from approximatelabs/tablib-v1-sample processed into graph representations.

Usage

from datasets import load_dataset
import graphtab

# Load the dataset
dataset = load_dataset("{full_repo_id}")

# Access a graph
graph_data = dataset['test'][0]

# Deserialize it
graph = graphtab.deserialize_graph(graph_data['graph_data'], graph_data['serialization'])

Citation

If you use this dataset, please cite both the original dataset and GraphTab.

Downloads last month
2