id stringlengths 32 32 | question stringlengths 20 359 | table_id stringlengths 1 30 | table dict | answer list |
|---|---|---|---|---|
502462f74e2b610c4df8e1cdbd7606b7 | what is the prevalence of formal recognition or letter of thanks in 2010? | 1293 | {
"cells": [
[
"type of formal employer support",
"2013",
"2010"
],
[
"",
"percentage",
""
],
[
"any type of support",
"55",
"57"
],
[
"use of facilities or equipment",
"27",
"30"
],
[
"paid time off or t... | [
"24.0"
] |
5fc37195b7f2c1b143daa0e27399d0bb | what is the prevalence of formal recognition or letter of thanks in 2013? | 1293 | {
"cells": [
[
"type of formal employer support",
"2013",
"2010"
],
[
"",
"percentage",
""
],
[
"any type of support",
"55",
"57"
],
[
"use of facilities or equipment",
"27",
"30"
],
[
"paid time off or t... | [
"19.0"
] |
b77473f060ec704ed3d59711b8eaa879 | what is the percentage of non-volunteers citing a lack of interest in volunteering in 2004? | 1294 | {
"cells": [
[
"",
"2013",
"2010",
"2007",
"2004"
],
[
"dissatified with previous volunteer experience",
"9",
"7",
"8",
"6"
],
[
"financial costs",
"18",
"17",
"18",
"15"
],
[
"did not know how ... | [
"23.0"
] |
469eb6f7e6e4001052fc7998908b0c1d | what is the percentage of non-volunteers citing a lack of interest in volunteering in 2013? | 1294 | {
"cells": [
[
"",
"2013",
"2010",
"2007",
"2004"
],
[
"dissatified with previous volunteer experience",
"9",
"7",
"8",
"6"
],
[
"financial costs",
"18",
"17",
"18",
"15"
],
[
"did not know how ... | [
"29.0"
] |
67e2a795b0837c1f72fd0daad317c2c8 | how many percentage points do health-related and personal care support drop since 2010 to 2013? | 1295 | {
"cells": [
[
"",
"2013",
"2010",
"2007",
"2004"
],
[
"housework, home maintenance",
"59",
"61",
"60",
"60"
],
[
"health-related or personal care",
"49",
"53",
"53",
"50"
],
[
"shopping, drivin... | [
"4"
] |
2afe5d3955d5e1d13912e90d1de30af3 | what is the entry rate of enterprises consisted of the group of short-lived firms? | 1297 | {
"cells": [
[
"entry type",
"firms",
"entries",
"entry rate",
"entry measured by employment",
"",
"",
"",
"",
"",
"",
"",
""
],
[
"",
"",
"",
"",
"alu employment creation rate",
"ilu employme... | [
"2.9"
] |
8e8487536896afec64d9650480e96bd0 | what is the total number of entrants in 2011? | 1297 | {
"cells": [
[
"entry type",
"firms",
"entries",
"entry rate",
"entry measured by employment",
"",
"",
"",
"",
"",
"",
"",
""
],
[
"",
"",
"",
"",
"alu employment creation rate",
"ilu employme... | [
"138506.0"
] |
734a809ea2180e3e832586cb58b45b40 | how many alus do entrants in 2011 account for? | 1297 | {
"cells": [
[
"entry type",
"firms",
"entries",
"entry rate",
"entry measured by employment",
"",
"",
"",
"",
"",
"",
"",
""
],
[
"",
"",
"",
"",
"alu employment creation rate",
"ilu employme... | [
"166580.0"
] |
b7367446c25c48d812945cdda5b471a4 | how many ilus do entrants in 2011 account for? | 1297 | {
"cells": [
[
"entry type",
"firms",
"entries",
"entry rate",
"entry measured by employment",
"",
"",
"",
"",
"",
"",
"",
""
],
[
"",
"",
"",
"",
"alu employment creation rate",
"ilu employme... | [
"305671.0"
] |
0dd16960c010011ed89561822cf12deb | how much percentage of employment using full-time equivalents do entrants account for if the first-year size of entrants is used? | 1297 | {
"cells": [
[
"entry type",
"firms",
"entries",
"entry rate",
"entry measured by employment",
"",
"",
"",
"",
"",
"",
"",
""
],
[
"",
"",
"",
"",
"alu employment creation rate",
"ilu employme... | [
"1.5"
] |
25a0cf9511c1a0b98a5db6dc649ea97f | how much percentage of employment using person-job counts do entrants account for if the first-year size of entrants is used? | 1297 | {
"cells": [
[
"entry type",
"firms",
"entries",
"entry rate",
"entry measured by employment",
"",
"",
"",
"",
"",
"",
"",
""
],
[
"",
"",
"",
"",
"alu employment creation rate",
"ilu employme... | [
"2.3"
] |
6c338421653d9acd1851f4ca7d64d13c | how much percentage of employment using full-time equivalents do entrants account for if the second-year size of entrants is used? | 1297 | {
"cells": [
[
"entry type",
"firms",
"entries",
"entry rate",
"entry measured by employment",
"",
"",
"",
"",
"",
"",
"",
""
],
[
"",
"",
"",
"",
"alu employment creation rate",
"ilu employme... | [
"1.3"
] |
eb70f1a23b2fa325af5116baaf901e8e | how much percentage of employment using person-job counts do entrants account for if the second-year size of entrants is used? | 1297 | {
"cells": [
[
"entry type",
"firms",
"entries",
"entry rate",
"entry measured by employment",
"",
"",
"",
"",
"",
"",
"",
""
],
[
"",
"",
"",
"",
"alu employment creation rate",
"ilu employme... | [
"1.9"
] |
c6d2b74ca863557a9217e3741a685bd2 | which club did ayanda nkili play for in 2013? | 129_totto15717-3 | {
"cells": [
[
"club",
"season",
"league",
"",
"",
"cup",
"",
"europe",
"",
"total",
""
],
[
"",
"",
"division",
"apps",
"goals",
"apps",
"goals",
"apps",
"goals",
"apps",
"g... | [
"orebro"
] |
be94d563493e06196b634ee9194af2dd | what was the peak chart position on the us of tons of sobs? | 129_totto15747-4 | {
"cells": [
[
"title",
"album details",
"peak chart positions",
"",
"",
""
],
[
"",
"",
"uk",
"ger",
"nor",
"us"
],
[
"tons of sobs",
"released: 14 march 1969 label: island format: lp",
"-",
"-",
... | [
"197.0"
] |
e809ae19ecffd62404bc5f916f5061d2 | how many million dollars of research and development performed by companies in the united states in 2013? | 12_114_tab1 | {
"cells": [
[
"industry and naics code",
"all r&d",
"paid for by the company",
"paid for by others"
],
[
"",
"",
"",
""
],
[
"all industries, 21-33, 42-81",
"322528",
"264913",
"57615"
],
[
"ict industries, 334,... | [
"322528.0"
] |
6da7cbf936aba7e003a6440c5c1a4243 | of the $323 billion of research and development performed by companies in the united states in 2013, how many percent did ict industries account for? | 12_114_tab1 | {
"cells": [
[
"industry and naics code",
"all r&d",
"paid for by the company",
"paid for by others"
],
[
"",
"",
"",
""
],
[
"all industries, 21-33, 42-81",
"322528",
"264913",
"57615"
],
[
"ict industries, 334,... | [
"0.413418"
] |
e6ea65b2cf26ff312854532eeb384890 | of the $323 million of research and development performed by companies in the united states in 2013, how many million dollars did ict industries account for? | 12_114_tab1 | {
"cells": [
[
"industry and naics code",
"all r&d",
"paid for by the company",
"paid for by others"
],
[
"",
"",
"",
""
],
[
"all industries, 21-33, 42-81",
"322528",
"264913",
"57615"
],
[
"ict industries, 334,... | [
"133339.0"
] |
0e926d3ba6f493dda88efb973846005f | how many times are r&d expenditures of ict industries larger than the pharmaceutical manufacturing industry, the single largest industry in terms of r&d expenditures in the united states? | 12_114_tab1 | {
"cells": [
[
"industry and naics code",
"all r&d",
"paid for by the company",
"paid for by others"
],
[
"",
"",
"",
""
],
[
"all industries, 21-33, 42-81",
"322528",
"264913",
"57615"
],
[
"ict industries, 334,... | [
"2.418857"
] |
ad68d927f4ebe66daf4133ac47c67f67 | how many goals did powell made with 42 league appearances in 2014-2015, for the milton keynes dons club? | 12_totto1364-0 | {
"cells": [
[
"club",
"season",
"league",
"",
"",
"fa cup",
"",
"league cup",
"",
"other",
"",
"total",
""
],
[
"",
"",
"division",
"apps",
"goals",
"apps",
"goals",
"apps",
... | [
"8.0"
] |
4fb571b9a6ce9fff39473e66bff028ca | in 2007, which album was relased by the war on drugs and had a song called "holding on"? | 12_totto1372-1 | {
"cells": [
[
"year",
"single",
"peak positions",
"",
"",
"",
"",
"",
"",
"",
"album"
],
[
"",
"",
"us aaa",
"us alt",
"us rock",
"bel",
"bel",
"can rock",
"mex air",
"ned",
... | [
"a deeper understanding"
] |
61f90b8b041fd8a3ae23e53e304705cd | what is the final result for the first viva world cup? | 12_totto1401-2 | {
"cells": [
[
"year",
"host",
"final",
"",
"",
"third place match",
"",
""
],
[
"",
"",
"winner",
"score",
"runner-up",
"3rd place",
"score",
"4th place"
],
[
"2006 details",
"occitania",
... | [
"21-1"
] |
91f06c00d632b2e70ef5a54ed4d0f524 | which year did chris calloway perform the best? | 12_totto1410-3 | {
"cells": [
[
"year",
"team",
"games",
"",
"receiving",
"",
"",
"",
"",
"rushing",
"",
"",
"",
"",
"fumbles",
""
],
[
"",
"",
"g",
"gs",
"rec",
"yds",
"avg",
"ln... | [
"1997.0"
] |
85b1cad37cc32edcf4317e6cfe61be1e | during the 1972-73 montreal canadiens season, what is the final result for canadiens? | 12_totto1420-4 | {
"cells": [
[
"nhl season",
"canadiens season",
"conference",
"division",
"regular season",
"",
"",
"",
"",
"",
"",
"",
"",
"postseason",
"",
"",
"",
"",
""
],
[
"",
"",
"",... | [
"1st"
] |
7e34d7cab8d8dcffb1dc9866cf3b8548 | which year has a higher number of under-reporters regardless of age or sex? | 13 | {
"cells": [
[
"",
"all",
"under-reporters",
"",
"",
"plausible reporters",
"",
"",
"over-reporters",
"",
""
],
[
"",
"",
"%",
"95% confidence interval",
"",
"%",
"95% confidence interval",
""... | [
"2015.0"
] |
f857c924f3f3086c975d60edff301f54 | how many times has the percentage of under-reporters increased in the youngest age group? | 13 | {
"cells": [
[
"",
"all",
"under-reporters",
"",
"",
"plausible reporters",
"",
"",
"over-reporters",
"",
""
],
[
"",
"",
"%",
"95% confidence interval",
"",
"%",
"95% confidence interval",
""... | [
"2.104478"
] |
d404577798c80e4ce775932c21fba950 | which group of people has been dereased from 2004 to 2015 significantly mostly? | 13 | {
"cells": [
[
"",
"all",
"under-reporters",
"",
"",
"plausible reporters",
"",
"",
"over-reporters",
"",
""
],
[
"",
"",
"%",
"95% confidence interval",
"",
"%",
"95% confidence interval",
""... | [
"over-reporters"
] |
8c8bdb6e9f29537e77c6552de940f993 | what is the most prevalent misreporting status? | 13 | {
"cells": [
[
"",
"all",
"under-reporters",
"",
"",
"plausible reporters",
"",
"",
"over-reporters",
"",
""
],
[
"",
"",
"%",
"95% confidence interval",
"",
"%",
"95% confidence interval",
""... | [
"plausible reporters"
] |
2da2d6ac5ea1d45d10462dd720f9ecf9 | what is the likelihood of being employed among off-reserve first nations mothers without a high school diploma who become mothers in their teens? | 1300 | {
"cells": [
[
"",
"aboriginal identity",
"",
""
],
[
"",
"off-reserve first nations",
"metis",
"inuit"
],
[
"",
"predicted probability",
"",
""
],
[
"motherhood status and high school completion",
"",
... | [
"0.4"
] |
607deb5bb0a513c4236daffa85ef1b6f | what is the likelihood of being employed among off-reserve first nations mothers without a high school diploma who become mothers later in life? | 1300 | {
"cells": [
[
"",
"aboriginal identity",
"",
""
],
[
"",
"off-reserve first nations",
"metis",
"inuit"
],
[
"",
"predicted probability",
"",
""
],
[
"motherhood status and high school completion",
"",
... | [
"0.41"
] |
fe6f23e21ab61c1b77124b7dd8e58b45 | what is the likelihood of being employed among off-reserve first nations early mothers with a diploma? | 1300 | {
"cells": [
[
"",
"aboriginal identity",
"",
""
],
[
"",
"off-reserve first nations",
"metis",
"inuit"
],
[
"",
"predicted probability",
"",
""
],
[
"motherhood status and high school completion",
"",
... | [
"0.59"
] |
0a7283a7703ab15e752b9a6a4caef850 | what is the likelihood of being employed among inuit women, those who have at least a high school diploma and who become mothers in their teenage years? | 1300 | {
"cells": [
[
"",
"aboriginal identity",
"",
""
],
[
"",
"off-reserve first nations",
"metis",
"inuit"
],
[
"",
"predicted probability",
"",
""
],
[
"motherhood status and high school completion",
"",
... | [
"0.67"
] |
cffbc73601dc949be8e9e5236bcb47a9 | which kind of inuit women have higher probability to be employed, women who had at least a high school diploma and who became mothers in their teenage years or early mothers who did not complete high school? | 1300 | {
"cells": [
[
"",
"aboriginal identity",
"",
""
],
[
"",
"off-reserve first nations",
"metis",
"inuit"
],
[
"",
"predicted probability",
"",
""
],
[
"motherhood status and high school completion",
"",
... | [
"early mothers, with diploma"
] |
7bd78aa1c36ef8c768939db9776c920b | which kind of inuit women are less likely to be employed, women without a diploma and without children or women who completed high school and were early mothers? | 1300 | {
"cells": [
[
"",
"aboriginal identity",
"",
""
],
[
"",
"off-reserve first nations",
"metis",
"inuit"
],
[
"",
"predicted probability",
"",
""
],
[
"motherhood status and high school completion",
"",
... | [
"childless women, no diploma"
] |
43f70713aab49d3bc57391bc4b9e620b | which characteristics of men cohort were slightly underrepresented among all the characteristics? | 1301 | {
"cells": [
[
"",
"men",
"",
"",
"",
"ratio",
"women",
"",
"",
"",
"ratio"
],
[
"",
"cohort",
"",
"in-scope",
"",
"",
"cohort",
"",
"in-scope",
"",
""
],
[
"",... | [
"not married or common-law",
"urban",
"moved"
] |
d3e55115aebf02529badddd44907ac51 | which characteristics of women cohort were slightly underrepresented among all the characteristics? | 1301 | {
"cells": [
[
"",
"men",
"",
"",
"",
"ratio",
"women",
"",
"",
"",
"ratio"
],
[
"",
"cohort",
"",
"in-scope",
"",
"",
"cohort",
"",
"in-scope",
"",
""
],
[
"",... | [
"not married or common-law",
"unemployed"
] |
f4b0186383b2f367a2197eb044e7e63e | which characteristics of men cohort were slightly overrepresented among all the characteristics? | 1301 | {
"cells": [
[
"",
"men",
"",
"",
"",
"ratio",
"women",
"",
"",
"",
"ratio"
],
[
"",
"cohort",
"",
"in-scope",
"",
"",
"cohort",
"",
"in-scope",
"",
""
],
[
"",... | [
"married or common-law",
"rural"
] |
ee2edabe566a1f6c6e78638b34f61eba | which characteristics of women cohort were slightly overrepresented among all the characteristics? | 1301 | {
"cells": [
[
"",
"men",
"",
"",
"",
"ratio",
"women",
"",
"",
"",
"ratio"
],
[
"",
"cohort",
"",
"in-scope",
"",
"",
"cohort",
"",
"in-scope",
"",
""
],
[
"",... | [
"married or common-law",
"moved",
"rural"
] |
ceafd1b878c8e8e5cb79881226a885f3 | by what percentage would families with a debt-to-asset ratio above 0.5 miss a non-mortagage payment? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"0.128"
] |
5cfab93ed5e0ad81fee54fd3255d625e | by what percentage would families with a debt-to-asset ratio above 0.25 and up to 0.50 miss a non-mortagage payment? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"0.122"
] |
f8a5f17bed0e3e9ec32cd2fd8b931c8a | by what percentage would families with a debt-to-asset ratio equal to or below 0.25 miss a non-mortagage payment? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"0.08"
] |
a7f818bc888dc2caa6a9757f959565aa | by what percentage would families owned their principal residence without mortgage miss a non-mortgage payment? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"0.078"
] |
3adab9b1b8efd91844a87ab4648cc295 | by what percentage would families who did not own their principal residence miss a non-mortgage payment? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"0.14"
] |
da1a3c9971346006772a5b2706eb07ad | by what percentage would families in the lowest income quintile skip or delay a non-mortgage payment? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"0.128"
] |
6792a3fc2b73ef66ec9e5134403aa866 | by what percentage would families in the fourth income quintile skip or delay a non-mortgage payment? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"0.095"
] |
498f490424592bf55fa26ba918e0aae7 | by what percentage would families in the fifth income quintile skip or delay a non-mortgage payment? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"0.051"
] |
0409176014c277bfa86649563e6f8e8f | by what percentage would families where the major income earner was aged 65 or over miss non-mortgage payment? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"0.062"
] |
44db9910b144605fd6c736f38b063a68 | by what percentage would families where the major income earner was aged 45 to 54 miss non-mortgage payment? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"0.125"
] |
b9c504dbd9190ade37be4c0367bccae0 | which kind of income earner were less likely to miss non-mortgage payments, university degree holders or high school diploma holders? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"university diploma or degree"
] |
c9c8f5ccb782fbd3fa2fe5d1ab937f01 | by what percentage would families in quebec skip or delay non-mortgage payment? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"0.136"
] |
50aa6767effa34ec9271a03215c2c589 | by what percentage would families in ontario skip or delay non-mortgage payment? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"0.096"
] |
4356602ba4a48bf2ab9d3198540e3423 | by what percentage would those in the lowest debt-to-asset ratio skip or delay a mortgage payment? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"0.016"
] |
6a33219953b114d1e9e0e5e15ce8eb2f | by what percentage would those with debt-to-asset ratios above 0.50 skip or delay a mortgage payment? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"0.073"
] |
885827c3bd29a665ad9a6421101ff557 | which family type had a higher probability of missing a mortgage payment, lone-parent families or couples without children? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"lone parent"
] |
007dcbff4cf29beb89093114c03cb532 | among all age groups of main income earner, which group was most likely to miss a mortgage payment? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"55 to 64 years"
] |
c30933389e49319ef8bd722f1fa21c59 | which age group of main income earner was less likely to miss a mortgage payment, families where the major income earner was 15 to 34 years old or families where the major income earner was 45 to 54 years old? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"15 to 34 years"
] |
2f560c125bec5da6d7d4c1855ae0e1d9 | which income group had a lower probability of missing a mortgage payment, families in the top income quintile (the fifth) or families in the bottom income quintile(the first)? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"fifth quintile"
] |
237a2c42f23af7ca2238a436286146e4 | regionally, which group of families were more likely to miss mortgage payment, families in the prairies or families in ontario? | 1305 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year",
"payday loan used in past three years"
],
[
"",
"predicted probability",
"",
""
],
[
"debt-to-asset ratio cat... | [
"prairies"
] |
4b5eefad1e2962babfee43ea088d5098 | by what percentage would families with a debt-to-asset ratio up to 0.25 skip or delay a non-mortgage payment? | 1307 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year"
],
[
"",
"predicted probability",
""
],
[
"debt-to-asset ratio category",
"",
""
],
[
"up to 0.2... | [
"0.048"
] |
4898b9ff874b24f80d12d4024c7707fa | by what percentage would families with a debt-to-asset ratio above o.5 skip or delay a non-mortgage payment? | 1307 | {
"cells": [
[
"",
"non-mortgage payment skipped or delayed in the past year",
"mortgage payment skipped or delayed in the past year"
],
[
"",
"predicted probability",
""
],
[
"debt-to-asset ratio category",
"",
""
],
[
"up to 0.2... | [
"0.098"
] |
a9dfe651e3c3df6c267d7d1ada589316 | which group of decendents were most among all the decedents who did not contact with police and had at least one contact with police in 24 monts prior to death, those who were not hospitalized, or those who had one or two more hospital visits in year prior to death? | 1309 | {
"cells": [
[
"type of health care involvement",
"no police contact in 24 months prior to death",
"at least one contact with police in 24 months prior to death"
],
[
"",
"percent",
""
],
[
"number of acute care hospital visits in year prior to death",
... | [
"none"
] |
50c44a9aab95a86c4e393061eafbfefa | among all the decedents who did not have contact with police in 24 months prior to deaths, what is the percentage of those who were not hospitalized in year prior to death? | 1309 | {
"cells": [
[
"type of health care involvement",
"no police contact in 24 months prior to death",
"at least one contact with police in 24 months prior to death"
],
[
"",
"percent",
""
],
[
"number of acute care hospital visits in year prior to death",
... | [
"75.0"
] |
a540fbc4e7e386bf2d8597389fbe2b78 | which group of decedents were more likely to have been hospitalized two or more times in the year before their death, those who had come into contact with police or those who hadn't come into contact with police? | 1309 | {
"cells": [
[
"type of health care involvement",
"no police contact in 24 months prior to death",
"at least one contact with police in 24 months prior to death"
],
[
"",
"percent",
""
],
[
"number of acute care hospital visits in year prior to death",
... | [
"at least one contact with police in 24 months prior to death"
] |
a62805fe9f4222b56f6c8460255161b3 | among decedents who had contact with police in 24 months prior to death, what is the percentage of those who were hospitalized at least once in the year before their death as a result of opioid poisoning? | 1309 | {
"cells": [
[
"type of health care involvement",
"no police contact in 24 months prior to death",
"at least one contact with police in 24 months prior to death"
],
[
"",
"percent",
""
],
[
"number of acute care hospital visits in year prior to death",
... | [
"5.0"
] |
7821d1fc7119f38ee53e23a9c30b06ef | among decedents who hadn't contact with police in 24 months prior to death, what is the percentage of those who were hospitalized at least once in the year before their death as a result of opioid poisoning? | 1309 | {
"cells": [
[
"type of health care involvement",
"no police contact in 24 months prior to death",
"at least one contact with police in 24 months prior to death"
],
[
"",
"percent",
""
],
[
"number of acute care hospital visits in year prior to death",
... | [
"4.0"
] |
a53c31d208960de5d96a01fb3a3a1a4f | how many billion dollars did basic research activities account for in 2016? | 130_62_np16-ib-19308-tab004 | {
"cells": [
[
"type of work",
"2000",
"2010",
"2012",
"2013",
"2014",
"2015",
"2016a",
"2017b"
],
[
"current $billions",
"",
"",
"",
"",
"",
"",
"",
""
],
[
"all r&d",
"267.9",
... | [
"88.6"
] |
c087257fd93d3ee12d64339a5eb4c348 | how many percentage points of total u.s. r&d expenditures did basic research activities account for? | 130_62_np16-ib-19308-tab004 | {
"cells": [
[
"type of work",
"2000",
"2010",
"2012",
"2013",
"2014",
"2015",
"2016a",
"2017b"
],
[
"current $billions",
"",
"",
"",
"",
"",
"",
"",
""
],
[
"all r&d",
"267.9",
... | [
"0.171939"
] |
355c456bbb78272db97de71f4ea7ac82 | how many billion dollars did applied research activities account for in 2016? | 130_62_np16-ib-19308-tab004 | {
"cells": [
[
"type of work",
"2000",
"2010",
"2012",
"2013",
"2014",
"2015",
"2016a",
"2017b"
],
[
"current $billions",
"",
"",
"",
"",
"",
"",
"",
""
],
[
"all r&d",
"267.9",
... | [
"104.6"
] |
e1b9017e08d6a4d7d561fa2df983ac50 | how many percentage points of total u.s. r&d expenditures did applied research activities account for? | 130_62_np16-ib-19308-tab004 | {
"cells": [
[
"type of work",
"2000",
"2010",
"2012",
"2013",
"2014",
"2015",
"2016a",
"2017b"
],
[
"current $billions",
"",
"",
"",
"",
"",
"",
"",
""
],
[
"all r&d",
"267.9",
... | [
"0.202989"
] |
7579cee13b6c92c4fbd44e3d906302b8 | how many billion dollars did experimental development activities account for in 2016? | 130_62_np16-ib-19308-tab004 | {
"cells": [
[
"type of work",
"2000",
"2010",
"2012",
"2013",
"2014",
"2015",
"2016a",
"2017b"
],
[
"current $billions",
"",
"",
"",
"",
"",
"",
"",
""
],
[
"all r&d",
"267.9",
... | [
"322.1"
] |
84cace18a468bc7e5b9f678448905f52 | how many percentage points of total u.s. r&d expenditures did experimental development activities account for? | 130_62_np16-ib-19308-tab004 | {
"cells": [
[
"type of work",
"2000",
"2010",
"2012",
"2013",
"2014",
"2015",
"2016a",
"2017b"
],
[
"current $billions",
"",
"",
"",
"",
"",
"",
"",
""
],
[
"all r&d",
"267.9",
... | [
"0.625073"
] |
d9fd73424337e4033cee443451e2034e | which club did shala play for in 2018? | 130_totto15758-0 | {
"cells": [
[
"club",
"season",
"league",
"",
"",
"cup",
"",
"europe",
"",
"other",
"",
"total",
""
],
[
"",
"",
"division",
"apps",
"goals",
"apps",
"goals",
"apps",
"goals... | [
"start"
] |
250e172543a7f8dbcdbc716293c3549a | how many points did adam vinatieri score in the postseason? | 130_totto15809-1 | {
"cells": [
[
"season",
"team",
"games",
"overall fgs",
"",
"",
"",
"",
"pats",
"",
"",
"",
"kickoffs",
"",
"",
"",
"",
"points"
],
[
"",
"",
"gp",
"blk",
"lng",
... | [
"238.0"
] |
eccfd08712bd3f1b5af941846dbf3ee2 | which club did wang xin play for in 2018? | 130_totto15937-3 | {
"cells": [
[
"club",
"season",
"league",
"",
"",
"national cup",
"",
"league cup",
"",
"continental",
"",
"total",
""
],
[
"",
"",
"division",
"apps",
"goals",
"apps",
"goals",
"... | [
"guangzhou r&f"
] |
cc2e0a2bc7a0821cf4354f99df4be0ad | how many rushing yards did wendell smallwood get in 2016? | 130_totto15956-4 | {
"cells": [
[
"year",
"team",
"games",
"",
"rushing",
"",
"",
"",
"",
"receiving",
"",
"",
"",
"",
"kick return",
"",
"",
""
],
[
"",
"",
"gp",
"gs",
"att",
"yds... | [
"312.0"
] |
faf496ced3d977d4e8bc8ec16353ec84 | among all decedents in british columbia and surrey, what is the percentage of those who experienced their fatal overdose within one year after their contact with police? | 1310 | {
"cells": [
[
"time period prior to fatal overdose",
"decedents in british columbia",
"decedents in surrey"
],
[
"",
"cumulative percent",
""
],
[
"1 month prior to fatal overdose",
"16",
"10"
],
[
"3 months prior to fatal overdo... | [
"75.0"
] |
7b67a0c7858b7ee4f607885faa06ec21 | among all decedents in british coulumbia who came into contact with police prior to their fatal overdose, what is the percentage of those who did so for a non-violent crime? | 1311 | {
"cells": [
[
"type of offence",
"police contacts for decedents in british columbia",
"police contacts for decedents in surrey",
"all criminal offences in british columbia, 2009 to 2016"
],
[
"",
"percent",
"",
""
],
[
"violent offences",
... | [
"83"
] |
1626cbe0177ea4b8d49d0469882c6327 | among all the types of offence, which type was the most common category of offence for which decedents had contact with police in the 24 months prior to their overdose both in british columbia and surrey? | 1311 | {
"cells": [
[
"type of offence",
"police contacts for decedents in british columbia",
"police contacts for decedents in surrey",
"all criminal offences in british columbia, 2009 to 2016"
],
[
"",
"percent",
"",
""
],
[
"violent offences",
... | [
"property offences"
] |
dea4fbb10740f60ead170a4f536d7160 | in 2017, how many individuals worldwide held a research doctoral degree in a science, engineering, or health (seh) field? | 131_64_sdr17-ib-19307-tab001 | {
"cells": [
[
"residence location",
"total",
"men",
"women",
"employment status",
"",
"",
"employment sector",
"",
""
],
[
"",
"",
"",
"",
"employed",
"unemployeda",
"not in the labor forceb",
"edu... | [
"1103200.0"
] |
6f325ee51e418208f9c677d04f8d2795 | how many individuals were residing in the united states? | 131_64_sdr17-ib-19307-tab001 | {
"cells": [
[
"residence location",
"total",
"men",
"women",
"employment status",
"",
"",
"employment sector",
"",
""
],
[
"",
"",
"",
"",
"employed",
"unemployeda",
"not in the labor forceb",
"edu... | [
"967500.0"
] |
bbec70ee31aaa709f1df7299dc1a49d3 | how many percent of individuals residing in the united states were women? | 131_64_sdr17-ib-19307-tab001 | {
"cells": [
[
"residence location",
"total",
"men",
"women",
"employment status",
"",
"",
"employment sector",
"",
""
],
[
"",
"",
"",
"",
"employed",
"unemployeda",
"not in the labor forceb",
"edu... | [
"0.349767"
] |
2fc43fc928165cc11b712f393ada3a9b | how many individuals residing in the united states were women? | 131_64_sdr17-ib-19307-tab001 | {
"cells": [
[
"residence location",
"total",
"men",
"women",
"employment status",
"",
"",
"employment sector",
"",
""
],
[
"",
"",
"",
"",
"employed",
"unemployeda",
"not in the labor forceb",
"edu... | [
"338400.0"
] |
71d9003c46144cece3d76403354c0f04 | how many individuals were living abroad? | 131_64_sdr17-ib-19307-tab001 | {
"cells": [
[
"residence location",
"total",
"men",
"women",
"employment status",
"",
"",
"employment sector",
"",
""
],
[
"",
"",
"",
"",
"employed",
"unemployeda",
"not in the labor forceb",
"edu... | [
"135700.0"
] |
df0890dd51311e9ef14d2951b7361889 | an additional 135,700 were living abroad, how many percent of whom were women? | 131_64_sdr17-ib-19307-tab001 | {
"cells": [
[
"residence location",
"total",
"men",
"women",
"employment status",
"",
"",
"employment sector",
"",
""
],
[
"",
"",
"",
"",
"employed",
"unemployeda",
"not in the labor forceb",
"edu... | [
"0.248342"
] |
d33db682d17e8fc1f79516ff9e011e88 | how many rushing yards did emmitt smith get in 1992? | 131_totto15986-0 | {
"cells": [
[
"year",
"team",
"games",
"",
"rushing",
"",
"",
"",
"",
"",
"",
"receiving",
"",
"",
"",
"",
"",
""
],
[
"",
"",
"gp",
"gs",
"att",
"yards",
... | [
"1713.0"
] |
ae4948aa9f19232b537448dd1cf47d87 | what the matches did benfica compete in the 2005-06 season? | 131_totto16008-1 | {
"cells": [
[
"no",
"pos",
"nat",
"player",
"total",
"",
"primeira liga",
"",
"taca de portugal",
"",
"champions league",
"",
"supertaca",
""
],
[
"",
"",
"",
"",
"apps",
"goals",
... | [
"primeira liga",
"taca de portugal",
"champions league"
] |
02f3716f1f5a436bdadb92dbb20189d1 | which club did geynrikh play for in 2015? | 131_totto16021-2 | {
"cells": [
[
"club",
"season",
"league",
"",
"",
"national cup",
"",
"league cup",
"",
"continental",
"",
"other",
"",
"total",
""
],
[
"",
"",
"division",
"apps",
"goals",
"apps... | [
"ordabasy"
] |
883a3552dba4f9de7b864f99321bf6d1 | which club did maric play for in 2015-16? | 131_totto16059-4 | {
"cells": [
[
"club",
"season",
"league",
"",
"",
"cup",
"",
"continental",
"",
"total",
""
],
[
"",
"",
"division",
"apps",
"goals",
"apps",
"goals",
"apps",
"goals",
"apps",
... | [
"persepolis"
] |
87b31a4cb71dd88bef8d73121057f5b3 | the most important contributor to total variance was person effects, what was the percentage of the variance of earnings for male workers? | 132 | {
"cells": [
[
"",
"male workers",
"female workers"
],
[
"",
"column 1",
"column 2"
],
[
"standard deviation of log earnings",
"0.575",
"0.499"
],
[
"number of person-year observations",
"39,572,671",
"20,738,690"
... | [
"58.1"
] |
395e1775e0baa1d69a9b65435efa0302 | the most important contributor to total variance was person effects, what was the percentage of the variance of earnings for female workers? | 132 | {
"cells": [
[
"",
"male workers",
"female workers"
],
[
"",
"column 1",
"column 2"
],
[
"standard deviation of log earnings",
"0.575",
"0.499"
],
[
"number of person-year observations",
"39,572,671",
"20,738,690"
... | [
"68.5"
] |
9c2a06819aba37a8eb34e98498608ab0 | the lower contribution of person effects for male workers was compensated by a higher contribution of the variance of predicted earnings based on observable characteristics and associated covariances, what was the percentage of the variance for male workers? | 132 | {
"cells": [
[
"",
"male workers",
"female workers"
],
[
"",
"column 1",
"column 2"
],
[
"standard deviation of log earnings",
"0.575",
"0.499"
],
[
"number of person-year observations",
"39,572,671",
"20,738,690"
... | [
"11.2"
] |
c454e5be0c141d6556300ebb61f0e9fe | the lower contribution of person effects for male workers was compensated by a higher contribution of the variance of predicted earnings based on observable characteristics and associated covariances, what was the percentage of the variance for female workers? | 132 | {
"cells": [
[
"",
"male workers",
"female workers"
],
[
"",
"column 1",
"column 2"
],
[
"standard deviation of log earnings",
"0.575",
"0.499"
],
[
"number of person-year observations",
"39,572,671",
"20,738,690"
... | [
"3.9"
] |
b13838157a31b9e8609e4a4b9fc9851f | what was the percentage of firm fixed effects for male workers? | 132 | {
"cells": [
[
"",
"male workers",
"female workers"
],
[
"",
"column 1",
"column 2"
],
[
"standard deviation of log earnings",
"0.575",
"0.499"
],
[
"number of person-year observations",
"39,572,671",
"20,738,690"
... | [
"11.1"
] |
0dd8be8b6648f2b558a70739bd0d1ff0 | what was the percentage of firm fixed effects for female workers? | 132 | {
"cells": [
[
"",
"male workers",
"female workers"
],
[
"",
"column 1",
"column 2"
],
[
"standard deviation of log earnings",
"0.575",
"0.499"
],
[
"number of person-year observations",
"39,572,671",
"20,738,690"
... | [
"11.3"
] |
ef09161468310693e3306eb00b7aa131 | what was the covariance between person and firm effect for male workers? | 132 | {
"cells": [
[
"",
"male workers",
"female workers"
],
[
"",
"column 1",
"column 2"
],
[
"standard deviation of log earnings",
"0.575",
"0.499"
],
[
"number of person-year observations",
"39,572,671",
"20,738,690"
... | [
"3.5"
] |
ffb366016c74287edfd351d48b2d2085 | what was the covariance between person and firm effect for female workers? | 132 | {
"cells": [
[
"",
"male workers",
"female workers"
],
[
"",
"column 1",
"column 2"
],
[
"standard deviation of log earnings",
"0.575",
"0.499"
],
[
"number of person-year observations",
"39,572,671",
"20,738,690"
... | [
"0.0"
] |
2e54ba30e524b53f6ec1bab43b5c68ea | which were the top three most frequently-mentioned sources of potential new capital among all the capital sources? | 1324 | {
"cells": [
[
"",
"very likely",
"somewhat likely",
"somewhat unlikely",
"very unlikely",
"total"
],
[
"",
"percent",
"",
"",
"",
""
],
[
"canadian private venture capital",
"26",
"13",
"29",
"32... | [
"personal finance",
"american private venture capital",
"angel investors"
] |
f99da192024a1c4e8597fd37378a9416 | which gender had a lower average annual earnings from wages, salaries and commissions in 2017, women or men? | 1325 | {
"cells": [
[
"",
"women",
"men",
"difference"
],
[
"",
"percent",
"",
""
],
[
"under $5,000",
"8.1",
"6.4",
"1.7"
],
[
"$5,000 to $9,999",
"8.4",
"5.8",
"2.6"
],
[
"$10,000 to $1... | [
"women"
] |
e6fb7bede1e8c774989d8ad405d52dc9 | what is the percentage of men who were in the total 20 occupations men in 2017? | 1327 | {
"cells": [
[
"occupations",
"women",
"men",
"difference"
],
[
"",
"percent",
"",
""
],
[
"mine service workers and operators in oil and gas drilling",
"0.01",
"0.08",
"0.08"
],
[
"central control and process op... | [
"11.52"
] |
4f04030fb1433edd5fa2e805c7841bfd | what is the percentage of decrease in the gender wage gap that occurred between 1997 and 2017 which was explained by changes in the relative characteristics of women and men? | 1328 | {
"cells": [
[
"change in real log gender wage ratio",
"-0.062"
],
[
"gender gap in log wages in 2017",
"0.134"
],
[
"gender gap in log wages in 1997",
"0.196"
],
[
"percent due to change in gender differences in characteristics",
"46.8"
... | [
"46.8"
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.