Datasets:

lewtun
/

my-awesome-dataset

Languages: English

Multilinguality: monolingual

Size Categories: 100K<n<1M

Language Creators: found

Annotations Creators: no-annotation

Source Datasets: original

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train · 891 rows

PassengerId int64 1 891	Survived int64 0 1	Pclass int64 1 3	Name stringlengths 12 82	Sex stringclasses 2 values	Age float64 0.42 80 ⌀	SibSp int64 0 8	Parch int64 0 6	Ticket stringlengths 3 18	Fare float64 0 512	Cabin stringlengths 1 15 ⌀	Embarked stringclasses 3 values
1	0	3	Braund, Mr. Owen Harris	male	22	1	0	A/5 21171	7.25	null	S
2	1	1	Cumings, Mrs. John Bradley (Florence Briggs Thayer)	female	38	1	0	PC 17599	71.2833	C85	C
3	1	3	Heikkinen, Miss. Laina	female	26	0	0	STON/O2. 3101282	7.925	null	S
4	1	1	Futrelle, Mrs. Jacques Heath (Lily May Peel)	female	35	1	0	113803	53.1	C123	S
5	0	3	Allen, Mr. William Henry	male	35	0	0	373450	8.05	null	S
6	0	3	Moran, Mr. James	male	null	0	0	330877	8.4583	null	Q
7	0	1	McCarthy, Mr. Timothy J	male	54	0	0	17463	51.8625	E46	S
8	0	3	Palsson, Master. Gosta Leonard	male	2	3	1	349909	21.075	null	S
9	1	3	Johnson, Mrs. Oscar W (Elisabeth Vilhelmina Berg)	female	27	0	2	347742	11.1333	null	S
10	1	2	Nasser, Mrs. Nicholas (Adele Achem)	female	14	1	0	237736	30.0708	null	C
11	1	3	Sandstrom, Miss. Marguerite Rut	female	4	1	1	PP 9549	16.7	G6	S
12	1	1	Bonnell, Miss. Elizabeth	female	58	0	0	113783	26.55	C103	S
13	0	3	Saundercock, Mr. William Henry	male	20	0	0	A/5. 2151	8.05	null	S
14	0	3	Andersson, Mr. Anders Johan	male	39	1	5	347082	31.275	null	S
15	0	3	Vestrom, Miss. Hulda Amanda Adolfina	female	14	0	0	350406	7.8542	null	S
16	1	2	Hewlett, Mrs. (Mary D Kingcome)	female	55	0	0	248706	16	null	S
17	0	3	Rice, Master. Eugene	male	2	4	1	382652	29.125	null	Q
18	1	2	Williams, Mr. Charles Eugene	male	null	0	0	244373	13	null	S
19	0	3	Vander Planke, Mrs. Julius (Emelia Maria Vandemoortele)	female	31	1	0	345763	18	null	S
20	1	3	Masselmani, Mrs. Fatima	female	null	0	0	2649	7.225	null	C
21	0	2	Fynney, Mr. Joseph J	male	35	0	0	239865	26	null	S
22	1	2	Beesley, Mr. Lawrence	male	34	0	0	248698	13	D56	S
23	1	3	McGowan, Miss. Anna "Annie"	female	15	0	0	330923	8.0292	null	Q
24	1	1	Sloper, Mr. William Thompson	male	28	0	0	113788	35.5	A6	S
25	0	3	Palsson, Miss. Torborg Danira	female	8	3	1	349909	21.075	null	S
26	1	3	Asplund, Mrs. Carl Oscar (Selma Augusta Emilia Johansson)	female	38	1	5	347077	31.3875	null	S
27	0	3	Emir, Mr. Farred Chehab	male	null	0	0	2631	7.225	null	C
28	0	1	Fortune, Mr. Charles Alexander	male	19	3	2	19950	263	C23 C25 C27	S
29	1	3	O'Dwyer, Miss. Ellen "Nellie"	female	null	0	0	330959	7.8792	null	Q
30	0	3	Todoroff, Mr. Lalio	male	null	0	0	349216	7.8958	null	S
31	0	1	Uruchurtu, Don. Manuel E	male	40	0	0	PC 17601	27.7208	null	C
32	1	1	Spencer, Mrs. William Augustus (Marie Eugenie)	female	null	1	0	PC 17569	146.5208	B78	C
33	1	3	Glynn, Miss. Mary Agatha	female	null	0	0	335677	7.75	null	Q
34	0	2	Wheadon, Mr. Edward H	male	66	0	0	C.A. 24579	10.5	null	S
35	0	1	Meyer, Mr. Edgar Joseph	male	28	1	0	PC 17604	82.1708	null	C
36	0	1	Holverson, Mr. Alexander Oskar	male	42	1	0	113789	52	null	S
37	1	3	Mamee, Mr. Hanna	male	null	0	0	2677	7.2292	null	C
38	0	3	Cann, Mr. Ernest Charles	male	21	0	0	A./5. 2152	8.05	null	S
39	0	3	Vander Planke, Miss. Augusta Maria	female	18	2	0	345764	18	null	S
40	1	3	Nicola-Yarred, Miss. Jamila	female	14	1	0	2651	11.2417	null	C
41	0	3	Ahlin, Mrs. Johan (Johanna Persdotter Larsson)	female	40	1	0	7546	9.475	null	S
42	0	2	Turpin, Mrs. William John Robert (Dorothy Ann Wonnacott)	female	27	1	0	11668	21	null	S
43	0	3	Kraeff, Mr. Theodor	male	null	0	0	349253	7.8958	null	C
44	1	2	Laroche, Miss. Simonne Marie Anne Andree	female	3	1	2	SC/Paris 2123	41.5792	null	C
45	1	3	Devaney, Miss. Margaret Delia	female	19	0	0	330958	7.8792	null	Q
46	0	3	Rogers, Mr. William John	male	null	0	0	S.C./A.4. 23567	8.05	null	S
47	0	3	Lennon, Mr. Denis	male	null	1	0	370371	15.5	null	Q
48	1	3	O'Driscoll, Miss. Bridget	female	null	0	0	14311	7.75	null	Q
49	0	3	Samaan, Mr. Youssef	male	null	2	0	2662	21.6792	null	C
50	0	3	Arnold-Franchi, Mrs. Josef (Josefine Franchi)	female	18	1	0	349237	17.8	null	S
51	0	3	Panula, Master. Juha Niilo	male	7	4	1	3101295	39.6875	null	S
52	0	3	Nosworthy, Mr. Richard Cater	male	21	0	0	A/4. 39886	7.8	null	S
53	1	1	Harper, Mrs. Henry Sleeper (Myna Haxtun)	female	49	1	0	PC 17572	76.7292	D33	C
54	1	2	Faunthorpe, Mrs. Lizzie (Elizabeth Anne Wilkinson)	female	29	1	0	2926	26	null	S
55	0	1	Ostby, Mr. Engelhart Cornelius	male	65	0	1	113509	61.9792	B30	C
56	1	1	Woolner, Mr. Hugh	male	null	0	0	19947	35.5	C52	S
57	1	2	Rugg, Miss. Emily	female	21	0	0	C.A. 31026	10.5	null	S
58	0	3	Novel, Mr. Mansouer	male	28.5	0	0	2697	7.2292	null	C
59	1	2	West, Miss. Constance Mirium	female	5	1	2	C.A. 34651	27.75	null	S
60	0	3	Goodwin, Master. William Frederick	male	11	5	2	CA 2144	46.9	null	S
61	0	3	Sirayanian, Mr. Orsen	male	22	0	0	2669	7.2292	null	C
62	1	1	Icard, Miss. Amelie	female	38	0	0	113572	80	B28	null
63	0	1	Harris, Mr. Henry Birkhardt	male	45	1	0	36973	83.475	C83	S
64	0	3	Skoog, Master. Harald	male	4	3	2	347088	27.9	null	S
65	0	1	Stewart, Mr. Albert A	male	null	0	0	PC 17605	27.7208	null	C
66	1	3	Moubarek, Master. Gerios	male	null	1	1	2661	15.2458	null	C
67	1	2	Nye, Mrs. (Elizabeth Ramell)	female	29	0	0	C.A. 29395	10.5	F33	S
68	0	3	Crease, Mr. Ernest James	male	19	0	0	S.P. 3464	8.1583	null	S
69	1	3	Andersson, Miss. Erna Alexandra	female	17	4	2	3101281	7.925	null	S
70	0	3	Kink, Mr. Vincenz	male	26	2	0	315151	8.6625	null	S
71	0	2	Jenkin, Mr. Stephen Curnow	male	32	0	0	C.A. 33111	10.5	null	S
72	0	3	Goodwin, Miss. Lillian Amy	female	16	5	2	CA 2144	46.9	null	S
73	0	2	Hood, Mr. Ambrose Jr	male	21	0	0	S.O.C. 14879	73.5	null	S
74	0	3	Chronopoulos, Mr. Apostolos	male	26	1	0	2680	14.4542	null	C
75	1	3	Bing, Mr. Lee	male	32	0	0	1601	56.4958	null	S
76	0	3	Moen, Mr. Sigurd Hansen	male	25	0	0	348123	7.65	F G73	S
77	0	3	Staneff, Mr. Ivan	male	null	0	0	349208	7.8958	null	S
78	0	3	Moutal, Mr. Rahamin Haim	male	null	0	0	374746	8.05	null	S
79	1	2	Caldwell, Master. Alden Gates	male	0.83	0	2	248738	29	null	S
80	1	3	Dowdell, Miss. Elizabeth	female	30	0	0	364516	12.475	null	S
81	0	3	Waelens, Mr. Achille	male	22	0	0	345767	9	null	S
82	1	3	Sheerlinck, Mr. Jan Baptist	male	29	0	0	345779	9.5	null	S
83	1	3	McDermott, Miss. Brigdet Delia	female	null	0	0	330932	7.7875	null	Q
84	0	1	Carrau, Mr. Francisco M	male	28	0	0	113059	47.1	null	S
85	1	2	Ilett, Miss. Bertha	female	17	0	0	SO/C 14885	10.5	null	S
86	1	3	Backstrom, Mrs. Karl Alfred (Maria Mathilda Gustafsson)	female	33	3	0	3101278	15.85	null	S
87	0	3	Ford, Mr. William Neal	male	16	1	3	W./C. 6608	34.375	null	S
88	0	3	Slocovski, Mr. Selman Francis	male	null	0	0	SOTON/OQ 392086	8.05	null	S
89	1	1	Fortune, Miss. Mabel Helen	female	23	3	2	19950	263	C23 C25 C27	S
90	0	3	Celotti, Mr. Francesco	male	24	0	0	343275	8.05	null	S
91	0	3	Christmann, Mr. Emil	male	29	0	0	343276	8.05	null	S
92	0	3	Andreasson, Mr. Paul Edvin	male	20	0	0	347466	7.8542	null	S
93	0	1	Chaffee, Mr. Herbert Fuller	male	46	1	0	W.E.P. 5734	61.175	E31	S
94	0	3	Dean, Mr. Bertram Frank	male	26	1	2	C.A. 2315	20.575	null	S
95	0	3	Coxon, Mr. Daniel	male	59	0	0	364500	7.25	null	S
96	0	3	Shorney, Mr. Charles Joseph	male	null	0	0	374910	8.05	null	S
97	0	1	Goldschmidt, Mr. George B	male	71	0	0	PC 17754	34.6542	A5	C
98	1	1	Greenfield, Mr. William Bertram	male	23	0	1	PC 17759	63.3583	D10 D12	C
99	1	2	Doling, Mrs. John T (Ada Julia Bone)	female	34	0	1	231919	23	null	S
100	0	2	Kantor, Mr. Sinai	male	34	1	0	244367	26	null	S

End of preview. Expand in Dataset Viewer.

YAML Metadata Warning: The task_categories "conditional-text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, text2text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, 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-retrieval, time-series-forecasting, text-to-video, image-text-to-text, 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, other

YAML Metadata Warning: The task_ids "summarization" is not in the official list: acceptability-classification, entity-linking-classification, fact-checking, intent-classification, language-identification, multi-class-classification, multi-label-classification, multi-input-text-classification, natural-language-inference, semantic-similarity-classification, sentiment-classification, topic-classification, semantic-similarity-scoring, sentiment-scoring, sentiment-analysis, hate-speech-detection, text-scoring, named-entity-recognition, part-of-speech, parsing, lemmatization, word-sense-disambiguation, coreference-resolution, extractive-qa, open-domain-qa, closed-domain-qa, news-articles-summarization, news-articles-headline-generation, dialogue-modeling, dialogue-generation, conversational, language-modeling, text-simplification, explanation-generation, abstractive-qa, open-domain-abstractive-qa, closed-domain-qa, open-book-qa, closed-book-qa, slot-filling, masked-language-modeling, keyword-spotting, speaker-identification, audio-intent-classification, audio-emotion-recognition, audio-language-identification, multi-label-image-classification, multi-class-image-classification, face-detection, vehicle-detection, instance-segmentation, semantic-segmentation, panoptic-segmentation, image-captioning, image-inpainting, image-colorization, super-resolution, grasping, task-planning, tabular-multi-class-classification, tabular-multi-label-classification, tabular-single-column-regression, rdf-to-text, multiple-choice-qa, multiple-choice-coreference-resolution, document-retrieval, utterance-retrieval, entity-linking-retrieval, fact-checking-retrieval, univariate-time-series-forecasting, multivariate-time-series-forecasting, visual-question-answering, document-question-answering

Dataset Card for Demo

Dataset Summary

This is a demo dataset with two files train.csv and test.csv.

Load it by:

from datasets import load_dataset 
data_files = {"train": "train.csv", "test": "test.csv"} 
demo = load_dataset("stevhliu/demo", data_files=data_files)