Languages spoken in Virginia Beach city, VA

In October 2015, the U.S. Census Bureau released the "2009-2013 American Community Survey" which provides information on "languages spoken at home" and "ability to speak English for the Population 5 Years and Over" for the United States as a whole, states including Puerto Rico and Washington D.C., selected counties, and selected cities and urban areas. The following provides aggregated survey information on languages spoken in Virginia Beach city [VA]

Table showing languages spoken in Virginia Beach city, VA

Population 5 years and over
Speak only English at home
Speak a language other than English at home
OTHER INDO-EUROPEAN LANGUAGES

French (incl. Patois, Cajun)

French Creole

Italian

Portuguese (incl. Portuguese Creole)

German (incl. Luxembourgian)

Yiddish

Other West Germanic languages

Scandinavian languages

Greek

Russian

Polish

Serbo-Croatian languages

Other Slavic languages

Other Indic languages

Other Indo-European languages

ASIAN AND PACIFIC ISLAND LANGUAGES

Chinese (incl. Cantonese, Mandarin, other Chinese languages)

Other Asian languages

Tagalog

Other Pacific Island languages

ALL OTHER LANGUAGES

Navajo

Other Native North American languages

Other and unspecified languages

BY STATE
BY COUNTY
BY CITY

Language	Number of speakers	Margin of Error	Speak English less than "Very Well"	Margin of Error
Population 5 years and over	412,652	32	14,581	726
Speak only English at home	364,549	1,298	(X)	(X)
Speak a language other than English at home	48,103	1,301	14,581	726
SPANISH AND SPANISH CREOLE	16,817	848	4,550	520
Spanish	16,815	848	4,550	520
OTHER INDO-EUROPEAN LANGUAGES	10,487	943	2,246	399
French (incl Patois, Cajun)	1,845	335	316	119
French	1,815	329	315	119
Patois	(D)	(D)	(B)	-
French Creole	320	207	13	21
Italian	1,214	366	209	163
Portuguese (incl Portuguese Creole)	323	147	57	41
Portuguese	325	147	55	41
German (incl Luxembourgian)	1,879	343	324	143
German	1,880	343	325	143
Yiddish	5	12	(B)	-
Other West Germanic languages	246	126	26	33
Dutch	165	99	25	33
Afrikaans	80	76	(B)	-
Scandinavian languages	229	146	(B)	-
Swedish	55	53	(B)	-
Danish	65	64	(B)	-
Norwegian	20	37	(B)	-
Icelandic	90	97	(B)	-
Greek	575	165	90	75
Russian	930	293	361	135
Polish	209	158	42	45
Serbo-Croatian languages	218	147	64	56
Serbocroatian	95	107	40	51
Serbian	120	93	25	27
Other Slavic languages	240	161	73	69
Bielorussian	(D)	(D)	(B)	-
Ukrainian	(D)	(D)	(D)	(D)
Slovak	50	50	(D)	(D)
Bulgarian	145	136	(D)	(D)
Armenian	14	20	3	7
Persian	286	171	101	74
Hindi	209	130	76	64
Gujarati	506	244	217	168
Urdu	283	172	76	58
Other Indic languages	621	299	138	93
India nec3	30	50	25	41
Bengali	95	106	20	41
Panjabi	205	186	35	54
Marathi	55	63	(B)	-
Nepali	(D)	(D)	(B)	-
Sindhi	70	103	(B)	-
Pakistan nec3	90	154	(D)	(D)
Sinhalese	70	68	(D)	(D)
Other Indo-European languages	335	182	60	44
Jamaican Creole	85	125	(D)	(D)
Pidgin	35	35	(B)	-
Catalonian	(D)	(D)	(B)	-
Romanian	85	76	20	23
Irish Gaelic	(D)	(D)	(B)	-
Albanian	60	75	(D)	(D)
Lithuanian	(D)	(D)	(B)	-
Latvian	(D)	(D)	(B)	-
ASIAN AND PACIFIC ISLAND LANGUAGES	18,951	836	7,306	586
Chinese (incl Cantonese, Mandarin, other Chinese languages4)	1,943	409	1,013	233
Chinese	1,265	329	640	198
Cantonese	125	84	90	62
Mandarin	485	274	260	163
Formosan	45	35	(D)	(D)
Wu	(D)	(D)	(D)	(D)
Japanese	952	280	355	124
Korean	987	291	588	220
Mon-Khmer, Cambodian	78	75	63	71
Hmong	8	13	(B)	-
Thai	153	106	129	98
Laotian	14	22	(B)	-
Vietnamese	1,616	495	1,056	332
Other Asian languages	592	223	162	106
Kazakh	(D)	(D)	(D)	(D)
Uighur	(D)	(D)	(D)	(D)
Turkish	290	151	130	102
Telugu	140	112	(D)	(D)
Kannada	25	26	(B)	-
Malayalam	(D)	(D)	(B)	-
Tamil	95	102	(B)	-
Tagalog	11,865	866	3,712	453
Other Pacific Island languages	743	286	228	127
Bisayan	185	165	(B)	-
Sebuano	45	47	(D)	(D)
Ilocano	175	124	115	84
Bikol	70	53	(D)	(D)
Pampangan	(D)	(D)	(D)	(D)
Chamorro	65	80	30	49
Marshallese	(D)	(D)	(B)	-
Tongan	145	178	(B)	-
ALL OTHER LANGUAGES	1,848	445	479	160
Other Native North American languages	67	79	(B)	-
Potawatomi	(D)	(D)	(B)	-
Mohawk	45	71	(B)	-
Hungarian	71	74	36	49
Arabic	463	194	152	86
Hebrew	114	73	10	16
African languages	1,073	415	272	142
Amharic	190	140	85	104
Chadic	(D)	(D)	(B)	-
Cushite	(D)	(D)	(B)	-
Nilotic	(D)	(D)	(D)	(D)
Swahili	180	131	50	50
Bantu	(D)	(D)	(B)	-
Mande	(D)	(D)	(D)	(D)
Fulani	(D)	(D)	(B)	-
Kru, Ibo, Yoruba	575	394	100	97
African	(D)	(D)	(B)	-
Other and unspecified languages	60	59	9	14
Finnish	(D)	(D)	(B)	-
Estonian	35	50	(D)	(D)
Uncodable	(D)	(D)	(B)	-

Notes

Number of speakers and Speak English less than "Very Well": Detailed-language estimates are rounded to the nearest multiple of five. Aggregate estimates ("language category" and "language sub-category" entries) are unrounded and appear in table B16001. Detailed-language estimates may not sum to aggregate estimates because of rounding.
Margin of Error and Margin of Error: Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data. The effect of nonsampling error is not represented in these tables.
(D): Data withheld to avoid disclosure.
(B): Either no sample observations or too few sample observations were available to compute an estimate.
(X): Question does not apply.
-: Either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.
3 N.E.C. stands for not elsewhere classified. These are languages where respondents indicated they spoke either Indian or Pakistan. For Indian, it cannot be determined if the respondent spoke a native American language or spoke a language from India. For Pakistan, respondents wrote in Pakistan but it cannot be determined which one of the languages spoken in Pakistan is actually being spoken. To distinguish these languages, n.e.c. is used to indicated they are not classified in any other language code.
This category includes literal write-ins of Chinese as well as Hakka, Kan, Hsiang, Cantonese, Mandarin, Fuchow, Formosan, and Wu.