Datasetpublic

SpiceeChat/Genre-Classifier-Country-Per-Country

Name Dataset — Gender Classifier Parquet Parquet conversion of philipperemy/name-dataset for first-name gender classification. Source Original repository: https://github.com/philipperemy/name-dataset Original archive: name_dataset.zip Original CSV format: first_name,last_name,gender,country_code Converted format: first_name,gender One Hugging Face config/subset per country code. Cleaning Rows are removed when: first_name is null, empty, or… See the full description on the dataset page: https://huggingface.co/datasets/SpiceeChat/Genre-Classifier-Country-Per-Country.

sourceHugging Faceotherupdated 3mo agoView on Hugging Face

1likes415downloads

Dataset Card

Name Dataset — Gender Classifier Parquet

Parquet conversion of philipperemy/name-dataset for first-name gender classification.

Source

—Original repository: https://github.com/philipperemy/name-dataset
—Original archive: name_dataset.zip
—Original CSV format: first_name,last_name,gender,country_code
—Converted format: first_name,gender
—One Hugging Face config/subset per country code.

Cleaning

Rows are removed when:

—first_name is null, empty, or whitespace-only
—gender is null, empty, or whitespace-only

Dataset structure

Each subset contains one split:

text

train

Columns:

text

first_name: string
gender: string

Conversion summary

—Parquet compression: zstd
—Converted subsets: 105
—Failed subsets: 0
—Total kept rows: 398 257 282
—Total dropped rows: 93 398 643

Subsets

Config	File	Kept rows	Dropped rows	Size
`AE`	`AE.parquet`	6 632 394	160 379	31.22 MB
`AF`	`AF.parquet`	493 392	64 935	2.28 MB
`AL`	`AL.parquet`	474 766	31 816	1.22 MB
`AO`	`AO.parquet`	466 139	42 612	2.97 MB
`AR`	`AR.parquet`	2 275 941	63 294	7.13 MB
`AT`	`AT.parquet`	1 162 065	87 230	2.87 MB
`AZ`	`AZ.parquet`	90 490	8 965	245.89 KB
`BD`	`BD.parquet`	3 419 547	373 778	15.60 MB
`BE`	`BE.parquet`	2 935 085	248 004	9.32 MB
`BF`	`BF.parquet`	5 582	831	25.33 KB
`BG`	`BG.parquet`	405 584	26 332	1.03 MB
`BH`	`BH.parquet`	4	1 416 043	786 B
`BI`	`BI.parquet`	13 968	1 739	63.91 KB
`BN`	`BN.parquet`	199 366	14 197	906.87 KB
`BO`	`BO.parquet`	2 627 499	325 656	9.33 MB
`BR`	`BR.parquet`	7 769 246	284 587	29.44 MB
`BW`	`BW.parquet`	235 643	4 941	1.07 MB
`CA`	`CA.parquet`	2 970 593	522 139	10.24 MB
`CH`	`CH.parquet`	1 434 446	157 426	4.88 MB
`CL`	`CL.parquet`	6 492 798	395 551	22.69 MB
`CM`	`CM.parquet`	1 974 466	23 086	9.08 MB
`CN`	`CN.parquet`	596 322	29 276	2.31 MB
`CO`	`CO.parquet`	17 252 297	705 193	62.55 MB
`CR`	`CR.parquet`	1 400 685	63 188	4.14 MB
`CY`	`CY.parquet`	107 788	11 198	361.46 KB
`CZ`	`CZ.parquet`	1 281 311	94 629	2.48 MB
`DE`	`DE.parquet`	5 661 086	392 521	14.64 MB
`DJ`	`DJ.parquet`	12 385	1 934	65.20 KB
`DK`	`DK.parquet`	560 269	79 526	1.53 MB
`DZ`	`DZ.parquet`	31	11 478 324	1.99 KB
`EC`	`EC.parquet`	281 448	36 005	891.07 KB
`EE`	`EE.parquet`	81 711	5 818	208.43 KB
`EG`	`EG.parquet`	44 145 642	1 021 565	60.46 MB
`ES`	`ES.parquet`	10 353 581	537 630	27.51 MB
`ET`	`ET.parquet`	11 130	1 622	60.70 KB
`FI`	`FI.parquet`	1 208 982	172 444	2.83 MB
`FJ`	`FJ.parquet`	4 326	1 036	22.91 KB
`FR`	`FR.parquet`	18 145 306	1 699 758	58.28 MB
`GB`	`GB.parquet`	10 250 723	1 268 505	25.37 MB
`GE`	`GE.parquet`	85 551	8 425	247.42 KB
`GH`	`GH.parquet`	869 033	158 862	3.28 MB
`GR`	`GR.parquet`	556 225	61 356	1.77 MB
`GT`	`GT.parquet`	1 414 758	230 261	5.05 MB
`HK`	`HK.parquet`	2 617 619	229 210	10.55 MB
`HN`	`HN.parquet`	12 865	2 962	50.45 KB
`HR`	`HR.parquet`	599 220	59 875	1.19 MB
`HT`	`HT.parquet`	13 785	1 622	73.94 KB
`HU`	`HU.parquet`	347 343	29 627	882.46 KB
`ID`	`ID.parquet`	115 336	14 931	469.04 KB
`IE`	`IE.parquet`	1 307 668	141 860	2.86 MB
`IL`	`IL.parquet`	3 751 051	204 930	13.22 MB
`IN`	`IN.parquet`	6 106 112	55 479	25.36 MB
`IQ`	`IQ.parquet`	16 633 966	186 717	26.21 MB
`IR`	`IR.parquet`	2 937 558	119 837	6.65 MB
`IS`	`IS.parquet`	26 508	4 835	91.22 KB
`IT`	`IT.parquet`	33 792 268	1 762 089	81.06 MB
`JM`	`JM.parquet`	355 772	30 073	1.13 MB
`JO`	`JO.parquet`	3 033 613	72 117	12.03 MB
`JP`	`JP.parquet`	392 434	34 274	1.35 MB
`KH`	`KH.parquet`	2 274	485	14.27 KB
`KR`	`KR.parquet`	115 838	3 967	362.45 KB
`KW`	`KW.parquet`	3 518 657	122 907	6.93 MB
`KZ`	`KZ.parquet`	3 174 836	38 143	11.36 MB
`LB`	`LB.parquet`	2	1 819 896	701 B
`LT`	`LT.parquet`	204 043	16 099	448.19 KB
`LU`	`LU.parquet`	171 250	16 820	525.13 KB
`LY`	`LY.parquet`	11	4 195 507	1.13 KB
`MA`	`MA.parquet`	40 034	17 416 911	39.76 KB
`MD`	`MD.parquet`	41 928	4 300	110.33 KB
`MO`	`MO.parquet`	378 160	19 820	1.48 MB
`MT`	`MT.parquet`	108 052	7 258	319.97 KB
`MU`	`MU.parquet`	799 279	49 223	2.72 MB
`MV`	`MV.parquet`	82 023	4 290	335.53 KB
`MX`	`MX.parquet`	12 930 995	399 224	41.45 MB
`MY`	`MY.parquet`	11 146 873	462 259	51.69 MB
`NA`	`NA.parquet`	395 677	13 600	1.82 MB
`NG`	`NG.parquet`	8 762 771	237 018	37.64 MB
`NL`	`NL.parquet`	5 121 203	307 955	14.48 MB
`NO`	`NO.parquet`	409 282	66 500	1.24 MB
`OM`	`OM.parquet`	4 952 758	95 189	8.67 MB
`PA`	`PA.parquet`	1 453 705	47 996	5.08 MB
`PE`	`PE.parquet`	7 850 726	224 200	31.65 MB
`PH`	`PH.parquet`	840 680	56 814	3.78 MB
`PL`	`PL.parquet`	2 547 684	121 618	4.41 MB
`PR`	`PR.parquet`	126 284	11 896	378.17 KB
`PS`	`PS.parquet`	3 228 830	138 075	4.26 MB
`PT`	`PT.parquet`	2 118 373	158 851	4.98 MB
`QA`	`QA.parquet`	2 468 668	84 954	4.66 MB
`RS`	`RS.parquet`	147 097	15 776	371.71 KB
`RU`	`RU.parquet`	9 849 944	142 742	24.36 MB
`SA`	`SA.parquet`	28 340 308	460 245	51.85 MB
`SD`	`SD.parquet`	9 370 894	92 302	61.54 MB
`SE`	`SE.parquet`	958 076	134 020	2.22 MB
`SG`	`SG.parquet`	2 829 254	206 594	12.80 MB
`SI`	`SI.parquet`	207 295	21 739	541.61 KB
`SV`	`SV.parquet`	3 763	716	16.34 KB
`SY`	`SY.parquet`	9	6 924 142	1.43 KB
`TM`	`TM.parquet`	16 061	215	61.73 KB
`TN`	`TN.parquet`	14	6 229 547	1.16 KB
`TR`	`TR.parquet`	9	19 458 325	1.73 KB
`TW`	`TW.parquet`	640 170	65 902	3.08 MB
`US`	`US.parquet`	29 278 534	3 030 439	95.24 MB
`UY`	`UY.parquet`	1 456 027	53 262	3.70 MB
`YE`	`YE.parquet`	8	4 600 715	1.12 KB
`ZA`	`ZA.parquet`	13 766 201	557 132	67.59 MB

Citation

bibtex

@misc{NameDataset2021,
  author = {Philippe Remy},
  title = {Name Dataset},
  year = {2021},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/philipperemy/name-dataset}},
}

Legal / privacy note

The original dataset states that each record is a real person. This converted version removes last_name and keeps only first_name and gender for classifier training.