Fedora Language Progression

The Data

library(tidyverse)
library(trend)
library(gt)

theme_set(theme_bw())

data <- read_csv('data_raw/computed_metrics.csv',
                 show_col_types = FALSE,
                 progress = FALSE)

New names:
• `` -> `...1`

data_prepared <- data |>
  select(language, release, translated_words)

data_prepared <- data_prepared |>
  mutate(
    release  = fct_reorder(release, parse_number(release)),
    language = factor(language)
  ) |>
  arrange(language, release)

Global overview

p <- data_prepared |>
  ggplot(aes(x = release,
             y = translated_words,
             group = language)) +
  geom_line(alpha = 0.3) +
  scale_y_continuous(breaks = c(1000, 10000, 1000000, 10000000, 100000000),
                     labels = scales::label_comma())

p

Inspection of “drops to zero”

zero_drops <- data_prepared |>
  group_by(language) |>
  arrange(release, .by_group = TRUE) %>%
  mutate(
    the_prev = lag(translated_words)
  ) %>%
  ungroup() %>%
  filter(
    translated_words == 0,
    coalesce(the_prev, 0) > 0
  )

zero_drops <- zero_drops |>
  mutate(big_drop = the_prev > 100)

languages_with_issue <- zero_drops|>
  filter(big_drop) |>
  distinct(language)

df_with_issue_releases <- data_prepared %>%
  semi_join(languages_with_issue, by = "language")

Releases with drops to zero:

df_with_issue_releases |> gt()

language	release	translated_words
ace	f10	412
ace	f11	443
ace	f12	405
ace	f13	405
ace	f14	405
ace	f24	0
ace	f25	0
ace	f26	0
ace	f27	0
ace	f28	0
ace	f29	0
ace	f30	0
ace	f31	0
ace	f32	0
ace	f33	0
ace	f34	0
ace	f35	0
ace	f36	0
ace	f37	0
ace	f38	0
ace	f39	0
ace	f40	0
ace	f41	0
ace	f42	0
ace	f43	0
ee	f7	1442
ee	f8	1454
ee	f9	1442
ee	f10	1442
ee	f13	1173
ee	f14	1173
ee	f15	1173
ee	f16	1173
ee	f17	1173
ee	f18	1173
ee	f25	0
ee	f26	0
ee	f27	0
ee	f28	0
ee	f29	0
ee	f30	0
ee	f31	0
ee	f32	0
ee	f33	0
ee	f34	0
ee	f35	29
ee	f36	0
ee	f37	0
ee	f38	0
ee	f39	29
ee	f40	29
ee	f41	29
ee	f42	29
ee	f43	29
jbo	f7	2152
jbo	f8	2152
jbo	f9	2152
jbo	f10	0
jbo	f11	0
jbo	f12	2
jbo	f13	2
jbo	f14	2
jbo	f15	4
jbo	f16	4
jbo	f17	4
jbo	f18	4
jbo	f19	4
jbo	f20	4
jbo	f21	4
jbo	f22	197
jbo	f23	231
jbo	f24	405
jbo	f25	430
jbo	f26	430
jbo	f27	430
jbo	f28	430
jbo	f29	427
jbo	f30	709
jbo	f31	709
jbo	f32	1027
jbo	f33	1027
jbo	f34	1027
jbo	f35	1043
jbo	f36	765
jbo	f37	765
jbo	f38	716
jbo	f39	1249
jbo	f40	1249
jbo	f41	1207
jbo	f42	3185
jbo	f43	3185
ng	f17	588
ng	f18	588
ng	f19	588
ng	f20	588
ng	f21	588
ng	f22	588
ng	f23	588
ng	f24	588
ng	f25	588
ng	f26	588
ng	f27	588
ng	f28	588
ng	f29	588
ng	f30	588
ng	f31	0
ng	f32	0
ng	f33	0
ng	f34	0
ng	f35	0
ng	f36	0
ng	f37	0
ng	f38	0
ng	f39	0
ng	f40	0
ng	f41	0
ng	f42	0
ng	f43	0
oj	f10	204
oj	f11	204
oj	f12	204
oj	f13	179
oj	f14	179
oj	f15	179
oj	f16	179
oj	f17	179
oj	f18	179
oj	f19	179
oj	f20	179
oj	f21	179
oj	f22	179
oj	f23	179
oj	f24	212
oj	f25	212
oj	f26	212
oj	f27	211
oj	f28	32
oj	f29	211
oj	f30	211
oj	f31	211
oj	f32	211
oj	f33	211
oj	f34	211
oj	f35	208
oj	f36	176
oj	f37	176
oj	f38	176
oj	f39	176
oj	f40	0
oj	f41	176
oj	f42	176
oj	f43	0
ss	f7	3633
ss	f8	3633
ss	f9	3633
ss	f16	49906
ss	f17	47423
ss	f18	45957
ss	f19	42722
ss	f20	38242
ss	f21	34876
ss	f22	32109
ss	f23	33972
ss	f24	33576
ss	f25	32427
ss	f26	31316
ss	f27	28663
ss	f28	31169
ss	f29	30799
ss	f30	30746
ss	f31	30482
ss	f32	0
ss	f33	30107
ss	f34	0
ss	f35	29864
ss	f36	29782
ss	f37	29607
ss	f38	29212
ss	f39	29120
ss	f40	28922
ss	f41	28857
ss	f42	29023
ss	f43	28754
tn	f16	36753
tn	f17	35864
tn	f18	34401
tn	f19	31422
tn	f20	27711
tn	f21	25044
tn	f22	22818
tn	f23	24419
tn	f24	24249
tn	f25	23200
tn	f26	22573
tn	f27	20521
tn	f28	23287
tn	f29	22902
tn	f30	22856
tn	f31	22752
tn	f32	0
tn	f33	22420
tn	f34	0
tn	f35	22184
tn	f36	22056
tn	f37	21908
tn	f38	21807
tn	f39	21717
tn	f40	21544
tn	f41	21487
tn	f42	21677
tn	f43	21429
to	f14	0
to	f15	0
to	f16	55
to	f17	56
to	f18	70
to	f19	71
to	f20	71
to	f21	193
to	f22	193
to	f23	194
to	f24	194
to	f25	194
to	f26	319
to	f27	319
to	f28	322
to	f29	321
to	f30	133
to	f31	325
to	f32	325
to	f33	325
to	f34	324
to	f35	0
to	f36	324
to	f37	324
to	f38	323
to	f39	323
to	f40	323
to	f41	323
to	f42	323
to	f43	323
tw	f8	587
tw	f9	587
tw	f10	548
tw	f11	548
tw	f12	548
tw	f13	489
tw	f14	489
tw	f15	489
tw	f16	489
tw	f17	489
tw	f18	489
tw	f19	489
tw	f20	489
tw	f21	489
tw	f22	475
tw	f23	475
tw	f24	475
tw	f25	475
tw	f26	475
tw	f27	475
tw	f28	0
tw	f29	475
tw	f30	475
tw	f31	1413
tw	f32	1301
tw	f33	1301
tw	f34	1301
tw	f35	1291
tw	f36	1291
tw	f37	1291
tw	f38	1291
tw	f39	1291
tw	f40	938
tw	f41	1284
tw	f42	1284
tw	f43	938

Analysis: trends

Currently ignoring the time-stamps. To be added later if need be.

We use Theil-Sen for trend estimation.

• Theil-Sen estimator (wikipedia)
• The R function used

data_prepared <- data_prepared |>
  add_count(language, name = "nb_releases")

res_trend <- data_prepared |>
  filter(nb_releases > 1) |>
  group_by(language) |>
  summarise(
    fit = list(sens.slope(translated_words)),
    slope = fit[[1]]$estimates,
    p_value = fit[[1]]$p.value,
    conf_low = fit[[1]]$conf.int[1],
    conf_high = fit[[1]]$conf.int[2],
    max_translated_words = max(translated_words),
    last_translated_words = last(translated_words),
    nb_releases_in_data = n(),
    .groups = "drop"
  )

# for sharing
res_trend |>
  select(language, last_translated_words,
         slope,
         p_value,
         conf_low, conf_high) |>
  arrange(desc(last_translated_words)) |>
  #arrange(desc(slope)) |>
  gt() |>
  fmt_number(
    columns = c(p_value),
    decimals = 2
  ) |>
  fmt_number(
    columns = c(slope, conf_low, conf_high),
    decimals = 0,
    use_seps = FALSE)    # Disable thousand separators

language	last_translated_words	slope	p_value	conf_low	conf_high
fr	12721173	292310	0.00	277788	304632
de	11571153	279628	0.00	263880	293046
es	10718286	259180	0.00	236747	275623
ru	10378786	249111	0.00	231455	263771
uk	8758076	229189	0.00	213011	243548
zh_Hans	8643032	210072	0.00	196854	218803
sv	7867560	169167	0.00	159076	180518
it	7818496	176819	0.00	162657	195256
pl	7577915	178465	0.00	167455	192978
ja	7257286	179722	0.00	165173	197058
pt_BR	7113597	171627	0.00	156179	189372
cs	5686372	138470	0.00	117848	150724
nl	5424688	129249	0.00	111683	137120
ko	5154472	137094	0.00	131183	142744
tr	5002600	118076	0.00	108476	128056
ca	4958397	134133	0.00	120309	141895
zh_Hant	4646383	109223	0.00	95587	123332
hu	4344007	96886	0.00	81160	109301
ro	4340052	67715	0.00	53676	82348
da	4315830	93796	0.00	74060	105781
fi	4038026	100274	0.00	78944	110907
en_GB	4025721	100242	0.00	82518	113747
el	4009201	96437	0.00	66667	110491
pt	4002448	102562	0.00	83073	114914
sr	3971261	87407	0.00	60212	106758
id	3456144	86801	0.00	68858	97736
gl	3348247	88922	0.00	75774	103672
sl	3326705	83230	0.00	67393	95468
bg	3103292	65370	0.00	56597	75462
eu	3069904	75829	0.00	64262	87040
sk	3032405	82544	0.00	68471	90377
nb_NO	2840028	62908	0.00	51709	69919
vi	2421812	51343	0.00	21420	62913
ar	2207700	51040	0.00	42871	56087
nn	2172183	58951	0.00	43314	66397
ca@valencia	2118721	71119	0.00	61438	79822
ka	2089654	16631	0.00	9363	28535
lt	2087389	59589	0.00	50810	65846
et	2050900	47411	0.00	34011	58014
eo	2035257	51493	0.00	44037	58743
ta	2004015	34957	0.00	27169	39455
he	1771439	38171	0.00	29822	46307
hr	1644461	44009	0.00	40733	46805
lv	1637006	43821	0.00	34505	50744
bs	1267866	41479	0.00	26274	50126
be	1127970	24202	0.00	21795	26434
ga	1124051	19974	0.00	15890	25485
hi	1028153	22254	0.00	15521	26780
th	911002	16868	0.00	11900	20176
ast	895210	17463	0.13	−2306	28201
is	886503	26475	0.00	22431	28810
ms	871599	24424	0.00	21842	26711
gu	843853	8621	0.40	−5358	17406
km	841480	21050	0.00	5222	30246
kk	813824	31116	0.00	22590	34944
mr	810286	17005	0.00	7261	23715
ne	801381	5416	0.35	−2229	15459
tl	800087	386	0.00	237	599
error	787307	−19769	0.02	−35601	−5471
mk	786531	3551	0.54	−5872	14706
pa	785959	11722	0.00	5079	14962
fa	781132	16349	0.00	13236	18596
es_AR	775151	17269	0.00	7972	25939
bn	770623	8353	0.30	−3524	20276
oc	769849	24082	0.00	22027	26396
pt_PT	720930	20754	0.00	15197	23971
bn_IN	701746	11250	0.27	−4889	17279
sq	678790	12206	0.00	7800	14639
sr_Latn	644082	10	1.00	−5905	7683
zh_Hant_HK	636080	15051	0.00	13456	16425
nds	603398	20730	0.00	14539	24217
hsb	602570	10517	0.00	7084	15994
dz	590018	−3309	0.44	−11054	7763
ml	589737	10281	0.00	4259	13744
kn	581106	8002	0.03	559	15306
ug	574417	14272	0.00	5526	19851
te	568762	8413	0.17	−2987	14861
as	568141	9121	0.03	1600	14168
en	559254	14894	0.00	13257	16557
cy	547558	9026	0.00	5121	11150
am	547117	18457	0.00	12832	22739
ia	531015	20352	0.00	16971	23088
dsb	526688	34522	0.00	23956	42892
af	526669	9049	0.00	6923	11085
sa	515383	1437	0.01	237	4403
or	483694	5170	0.27	−2411	10600
hy	471820	9762	0.00	8604	11144
az	460940	9749	0.00	7476	12614
gd	436124	17924	0.00	12946	21707
fur	422163	14179	0.00	12760	15697
en_CA	406745	2491	0.04	169	3888
br	378510	6888	0.00	3494	9672
sr@ijekavian	362877	6413	0.01	884	13221
tg	359457	6009	0.00	2492	11856
mai	319144	6161	0.00	2606	8963
sr@ijekavian_Latn	318994	1755	0.45	−1606	6508
om	306693	−7550	0.00	−7920	−6984
en_ZA	306541	−4906	0.35	−7528	519
uz	293967	5957	0.00	4355	6539
sid	281687	8738	0.08	0	11706
en_AU	276160	7362	0.00	5738	9030
fy	270918	8746	0.00	6556	9820
si	266807	3842	0.04	137	6706
es_MX	256485	3059	0.00	1928	4639
be_Latn	250600	1472	0.00	694	2028
mn	248734	2281	0.34	−1345	4038
bo	238941	−3541	0.42	−5702	434
kab	224774	7310	0.00	5498	8680
my	216388	3394	0.01	802	5412
xh	215729	1781	0.34	−1348	2765
an	190295	5598	0.00	3023	7372
fr_CA	186286	1876	0.00	1437	2648
en_US	184721	8776	0.00	4338	12063
ie	166170	10750	0.00	9683	11749
crh	160961	680	0.09	−88	1958
ab	143032	3081	0.00	1904	4645
grc	135423	0	0.51	−1	15000
wa	134366	3889	0.00	2730	4332
ur	128180	3460	0.00	2995	4346
mg	121347	980	0.00	329	1436
ku	120886	1472	0.00	736	2054
brx	119036	2030	0.00	1067	2642
szl	101553	4266	0.00	805	6114
vec	101531	182	0.18	−57	1334
hne	95449	1331	0.06	0	3059
ks	89609	1175	0.01	271	2428
nso	84553	166	0.78	−550	1399
mni	80790	−288	0.71	−981	825
kok	80618	2113	0.01	456	3151
he_IL	74693	1632	0.00	1178	1947
doi	74415	−201	0.74	−898	746
co	72109	2849	0.00	1522	3822
zu	70975	58	0.93	−1196	1252
sat	68863	130	0.69	−615	967
ckb	66568	2146	0.00	479	2790
la	63883	1242	0.01	306	1847
lo	62361	894	0.00	467	1955
ps	62083	350	0.00	116	676
sd	61759	913	0.01	93	2235
gug	60659	−197	0.13	−330	17
ky	58370	1362	0.00	853	1947
se	56856	1742	0.00	1470	1983
rw	56136	−5	0.93	−439	1203
sw	51760	720	0.00	585	918
de_AT	45188	−5	0.29	−47	41
tt	41055	902	0.00	506	1105
en_NZ	39524	71	0.00	2	1361
sw_TZ	38156	−533	0.00	−935	−338
nl_BE	37367	856	0.00	587	1236
sr_Cyrl	34940	1254	0.00	602	1605
li	33516	423	0.00	116	633
lg	33136	204	0.19	−71	699
kmr_Latn	32492	−618	0.00	−798	−417
ig	32268	657	0.00	534	754
yi	31026	450	0.00	280	604
csb	30702	1057	0.00	624	1265
ts	30168	−90	0.41	−250	601
ar_EG	29966	785	0.00	123	1620
yo	29751	572	0.00	422	787
ve	28832	−72	0.50	−215	797
ss	28754	−212	0.00	−419	−163
st	28465	−90	0.40	−282	728
nr	28234	−56	0.13	−213	523
ar_SA	26424	730	0.00	526	1035
sc	26015	3470	0.00	1754	4470
tok	25361	2615	0.01	36	3971
zh_Hans_SG	24828	113	0.00	39	2750
tk	23667	294	0.00	208	345
fil	23555	395	0.00	349	458
ha	23436	328	0.00	196	437
es_CO	22594	876	0.00	514	2005
tn	21429	−185	0.00	−530	−128
fo	20767	67	0.63	−168	340
lb	18579	341	0.00	117	603
de_CH	16629	−251	0.01	−520	−61
ur_PK	16321	38	0.44	−47	197
mjw	16076	220	0.01	53	578
su	15313	21	0.00	9	34
rue	14977	24	0.02	7	409
gv	14645	−37	0.08	−366	0
ach	13257	380	0.00	286	488
ay	13011	409	0.00	284	475
mhr	12713	−153	0.00	−174	−122
es_VE	12567	203	0.10	−266	410
mi	12139	251	0.03	17	333
ayc	11786	48	0.28	−26	135
kr	11636	164	0.00	21	449
kg	10686	378	0.00	292	458
qu	10205	155	0.00	28	246
ln	10058	311	0.00	13	443
io	10021	207	0.00	164	260
es_CL	9795	114	0.23	−142	251
es_419	9710	993	0.01	369	1957
ff	9257	141	0.00	24	204
kmr	9023	360	0.00	276	423
ru_UA	8677	203	0.00	150	244
pap	8045	159	0.01	23	271
ar_DZ	7799	250	0.00	9	457
ltg	7650	50	0.00	2	265
wo	7632	96	0.00	25	134
man	7361	−658	0.00	−1298	−212
za	6946	0	0.25	0	0
ht	6261	69	0.18	−34	117
son	6104	−15	0.65	−145	78
es_US	6021	120	0.00	0	300
cgg	5858	−29	0.05	−82	0
jv	5725	330	0.00	246	498
es_PE	5720	4	0.49	−42	41
ak	5496	−138	0.00	−207	−51
hus	5066	−21	0.09	−69	6
mnk	4994	0	0.03	0	0
bn_BD	4863	0	0.89	−506	64
es_NI	4679	−56	0.21	−86	22
es_PR	4559	−10	0.35	−68	24
bm	4274	−4	0.11	−31	0
ang	4107	24	0.60	−42	106
kw	3534	43	0.06	0	107
ar_LY	3529	−21	0.00	−44	−15
mt	3340	28	0.10	−8	72
jbo	3185	39	0.00	29	49
ro_MD	3179	134	0.02	0	208
gn	3110	57	0.00	15	122
ms_Arab	3092	−310	0.00	−386	−228
nap	2942	99	0.01	9	144
bin	2924	−32	0.03	−472	0
os	2873	161	0.00	88	212
es_DO	2487	−41	0.02	−74	−2
es_EC	2486	−39	0.26	−664	224
es_CR	2479	−142	0.00	−216	−23
es_PA	2479	−37	0.00	−61	−2
es_SV	2479	−37	0.00	−61	−2
es_UY	2479	−50	0.00	−65	−35
fr_BE	2471	−5	0.34	−38	4
krl	2432	−44	0.07	−94	0
frp	2300	86	0.00	50	109
sgs	2095	250	0.02	0	401
uz_Latn	1763	21	0.04	0	35
ti	1664	43	0.00	31	49
bi	1645	0	0.18	0	61
fr_CH	1603	−24	0.01	−47	−2
yue_Hant	1528	96	0.00	0	382
sm	1521	37	0.01	1	54
sco	1472	17	0.00	10	23
nah	1443	47	0.01	1	67
so	1410	−28	0.04	−39	0
kl	1360	12	0.21	−5	28
cv	1325	17	0.32	−16	34
zgh	1148	36	0.02	5	58
en_IE	1135	−10	0.00	−21	0
kv	1106	0	0.61	0	58
prs	1057	−157	0.00	−275	−99
pms	1017	39	0.00	34	44
tt@iqtelif	1015	−1	0.00	−1	−1
ckb_IR	942	−7	0.00	−14	−5
tw	938	0	0.42	−1	27
cpf	902	0	0.00	−1	0
dv	784	24	0.00	19	29
mnw	608	29	0.00	0	45
cnr	548	−436	0.00	−593	0
wae	535	4	0.02	0	8
shn	476	4	0.01	0	12
bal	471	−44	0.00	−56	−16
pa_PK	466	0	NaN	0	0
udm	442	0	0.92	−4	24
en@pirate	388	0	0.24	0	4
byn	386	0	0.00	0	0
gez	386	0	0.00	0	0
tig	386	0	0.00	0	0
isv	335	0	0.04	0	33
to	323	10	0.00	2	14
bar	303	0	0.67	0	0
ce	289	12	0.00	0	16
rm	259	5	0.00	4	8
jam	250	0	0.00	0	0
aa	237	7	0.00	0	11
en_Shaw	216	0	NaN	0	0
na	210	7	0.00	3	9
ber	209	3	0.01	0	7
pi	185	0	0.24	0	0
ilo	175	−107	0.00	−175	−15
nan_Hant	173	0	0.03	0	0
tlh	169	2	0.00	1	3
tzm	161	5	0.00	4	7
ki	144	0	0.67	0	0
wal	141	0	0.00	0	0
sn	128	0	0.20	0	0
chr	122	0	0.18	0	7
iu	117	150	0.00	62	188
tpi	114	1	0.38	0	5
nv	110	0	0.24	0	0
bem	97	1	0.00	0	1
sah	90	0	0.70	−2	3
tet	87	0	NaN	0	0
ar_MA	83	0	NaN	0	0
cak	81	0	0.00	0	0
sma	68	−2	0.40	−9	2
azb	36	1	0.00	0	1
ch	30	0	0.67	0	0
ee	29	−49	0.00	−65	0
nqo	25	0	0.00	0	1
tvl	23	0	0.96	0	0
haw	22	−3	0.00	−4	0
lzh	18	0	0.02	0	0
lmo	13	−3	0.05	−5	0
tyv	9	0	0.00	0	0
guc	8	0	0.00	−1	0
kos	6	0	0.01	0	0
en_IN	5	0	0.91	0	0
ban	4	0	0.00	0	0
gaa	4	0	0.16	0	0
mus	3	0	0.96	0	0
pam	3	−3	0.01	−11	0
cpp	2	0	0.44	0	0
rom	2	0	0.00	0	0
ace	0	0	0.00	0	0
ae	0	0	0.50	0	0
ain	0	0	NaN	0	0
aln	0	0	NaN	0	0
anp	0	0	NaN	0	0
av	0	0	0.31	0	0
ba	0	0	0.02	0	0
bh	0	0	0.04	0	0
bqi	0	0	NaN	0	0
cr	0	0	0.01	0	0
cu	0	0	NaN	0	0
enm	0	0	NaN	0	0
fj	0	0	NaN	0	0
ho	0	0	NaN	0	0
hz	0	0	NaN	0	0
ii	0	0	0.00	0	0
ik	0	0	NaN	0	0
kj	0	0	NaN	0	0
lfn	0	0	NaN	0	0
lu	0	0	NaN	0	0
mh	0	0	NaN	0	0
nd	0	0	NaN	0	0
ng	0	−26	0.00	−35	0
ny	0	0	NaN	0	0
oj	0	0	0.06	0	0
rn	0	0	NaN	0	0
sg	0	0	NaN	0	0
smj	0	0	NaN	NA	NA
ty	0	0	NaN	0	0
vo	0	0	NaN	0	0

Positive trends

noticeable_positive_trends <- res_trend |>
  filter(last_translated_words > 100000,
         p_value < 0.05,
         slope >= 20000)

noticeable_positive_trends |> 
  select(language, last_translated_words,
         slope,
         p_value,
         conf_low, conf_high) |>
  arrange(desc(last_translated_words)) |>
  #arrange(desc(slope)) |>
  gt() |>
  fmt_number(
    columns = c(p_value),
    decimals = 2
  ) |>
  fmt_number(
    columns = c(slope, conf_low, conf_high),
    decimals = 0,
    use_seps = FALSE)    # Disable thousand separators

language	last_translated_words	slope	p_value	conf_low	conf_high
fr	12721173	292310	0.00	277788	304632
de	11571153	279628	0.00	263880	293046
es	10718286	259180	0.00	236747	275623
ru	10378786	249111	0.00	231455	263771
uk	8758076	229189	0.00	213011	243548
zh_Hans	8643032	210072	0.00	196854	218803
sv	7867560	169167	0.00	159076	180518
it	7818496	176819	0.00	162657	195256
pl	7577915	178465	0.00	167455	192978
ja	7257286	179722	0.00	165173	197058
pt_BR	7113597	171627	0.00	156179	189372
cs	5686372	138470	0.00	117848	150724
nl	5424688	129249	0.00	111683	137120
ko	5154472	137094	0.00	131183	142744
tr	5002600	118076	0.00	108476	128056
ca	4958397	134133	0.00	120309	141895
zh_Hant	4646383	109223	0.00	95587	123332
hu	4344007	96886	0.00	81160	109301
ro	4340052	67715	0.00	53676	82348
da	4315830	93796	0.00	74060	105781
fi	4038026	100274	0.00	78944	110907
en_GB	4025721	100242	0.00	82518	113747
el	4009201	96437	0.00	66667	110491
pt	4002448	102562	0.00	83073	114914
sr	3971261	87407	0.00	60212	106758
id	3456144	86801	0.00	68858	97736
gl	3348247	88922	0.00	75774	103672
sl	3326705	83230	0.00	67393	95468
bg	3103292	65370	0.00	56597	75462
eu	3069904	75829	0.00	64262	87040
sk	3032405	82544	0.00	68471	90377
nb_NO	2840028	62908	0.00	51709	69919
vi	2421812	51343	0.00	21420	62913
ar	2207700	51040	0.00	42871	56087
nn	2172183	58951	0.00	43314	66397
ca@valencia	2118721	71119	0.00	61438	79822
lt	2087389	59589	0.00	50810	65846
et	2050900	47411	0.00	34011	58014
eo	2035257	51493	0.00	44037	58743
ta	2004015	34957	0.00	27169	39455
he	1771439	38171	0.00	29822	46307
hr	1644461	44009	0.00	40733	46805
lv	1637006	43821	0.00	34505	50744
bs	1267866	41479	0.00	26274	50126
be	1127970	24202	0.00	21795	26434
hi	1028153	22254	0.00	15521	26780
is	886503	26475	0.00	22431	28810
ms	871599	24424	0.00	21842	26711
km	841480	21050	0.00	5222	30246
kk	813824	31116	0.00	22590	34944
oc	769849	24082	0.00	22027	26396
pt_PT	720930	20754	0.00	15197	23971
nds	603398	20730	0.00	14539	24217
ia	531015	20352	0.00	16971	23088
dsb	526688	34522	0.00	23956	42892