id stringlengths 32 32 | table_id stringlengths 1 30 | table_source stringclasses 3
values | sentence_id stringlengths 1 5 | sub_sentence_id stringclasses 23
values | sub_sentence stringlengths 3 369 | question stringlengths 20 359 | answer stringlengths 3 215 | aggregation stringclasses 54
values | linked_cells stringlengths 112 1.84k | answer_formulas stringlengths 3 145 | reference_cells_map stringlengths 2 390 | table_html stringlengths 357 21.2k | table_texts listlengths 3 66 | table_hmt stringlengths 823 38.1k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
822d0514ad6c3058d70cffec53211837 | 0_totto74-1 | totto | 0 | 1 | in 2016 season, charles sims finished with 51 rushes for 149 yards. | in 2016 season, how many rushes did charles sims finish for 149 yards? | [51.0] | ["none"] | {"entity_link": {"top": {"rushes": {"(0, 4)": "rushing"}}, "left": {"in 2016": {"(4, 0)": 2016.0}}, "top_left_corner": {}}, "quantity_link": {"149": {"(4, 5)": 149.0}, "[ANSWER]": {"(4, 4)": 51.0}}} | ["=E7"] | {"E7": "(4, 4)"} | <table border='1' cellpadding='4' cellspacing='0'>
<tr>
<td rowspan='2'>season</td>
<td rowspan='2'>team</td>
<td colspan='2'>games</td>
<td colspan='5'>rushing</td>
<td colspan='5'>receiving</td>
<td colspan='2'>fumbles</td>
</tr>
<tr>
<td>gp</td>
<td>gs</td>
<td>att</td>
... | [
[
"season",
"team",
"games",
"",
"rushing",
"",
"",
"",
"",
"receiving",
"",
"",
"",
"",
"fumbles",
""
],
[
"",
"",
"gp",
"gs",
"att",
"yds",
"avg",
"lng",
"td",
"rec",
"yds",
"avg",
"lng",
"t... | {"title": "career statistics", "top_root": {"name": "<TOP>", "value": "<TOP>", "type": "string", "line_idx": null, "children_dict": [{"name": "games", "value": "games", "type": "string", "children_dict": [{"name": "gp", "value": "gp", "type": "string", "children_dict": [], "line_idx": 0}, {"name": "gs", "value": "gs", ... |
249b7a7903f9dec2873b2ff4eafb8075 | 0_totto109-3 | totto | 0 | 1 | schwartz was the manager of rot-weiß erfurt between 11 april 2003 and 30 june 2003 where he won one out of 10 matches. | how many games did schwartz, the manager of rot-weiß erfurt between 11 april 2003 and 30 june 2003, won out of 10 matches? | [1.0] | ["none"] | {"entity_link": {"top": {"matches": {"(1, 3)": "g"}, "won": {"(1, 4)": "w"}}, "left": {"rot-wei\u00df erfurt": {"(2, 0)": "rot-wei\u00df erfurt"}, "11 april 2003": {"(2, 1)": "11 april 2003"}, "30 june 2003": {"(2, 2)": "30 june 2003"}}, "top_left_corner": {}}, "quantity_link": {"10": {"(2, 3)": 10.0}, "[ANSWER]": {"(2... | ["=E5"] | {"E5": "(2, 4)"} | <table border='1' cellpadding='4' cellspacing='0'>
<tr>
<td rowspan='2'>team</td>
<td rowspan='2'>from</td>
<td rowspan='2'>to</td>
<td colspan='6'>record</td>
</tr>
<tr>
<td>g</td>
<td>w</td>
<td>d</td>
<td>l</td>
<td>win %</td>
<td>ref</td>
</tr>
<tr>
<td>rot-weiß... | [
[
"team",
"from",
"to",
"record",
"",
"",
"",
"",
""
],
[
"",
"",
"",
"g",
"w",
"d",
"l",
"win %",
"ref"
],
[
"rot-weiß erfurt",
"11 april 2003",
"30 june 2003",
"10",
"1",
"3",
"6",
"10.00",
"none"
... | {"title": "managerial record", "top_root": {"name": "<TOP>", "value": "<TOP>", "type": "string", "line_idx": null, "children_dict": [{"name": "record", "value": "record", "type": "string", "children_dict": [{"name": "g", "value": "g", "type": "string", "children_dict": [], "line_idx": 0}, {"name": "w", "value": "w", "t... |
57184793dfabcdd5a164e3c047a101e1 | 0_totto115-4 | totto | 0 | 1 | in total, craig finished his eleven nfl seasons with 8,189 rushing yards and 566 receptions for 4,911 receiving yards. | in total, how many rushing yards did craig finish during his eleven nfl seasons? | [8189.0] | ["none"] | {"entity_link": {"top": {"yards": {"(1, 3)": "yds"}, "rushing": {"(0, 1)": "rushing"}}, "left": {"in total": {"(13, 0)": "totals"}}, "top_left_corner": {}}, "quantity_link": {"566": {"(13, 7)": 566.0}, "4911": {"(13, 8)": 4911.0}, "eleven": {"(12, 5)": 11.0}, "[ANSWER]": {"(13, 3)": 8189.0}}} | ["=D16"] | {"D16": "(13, 3)"} | <table border='1' cellpadding='4' cellspacing='0'>
<tr>
<td>none</td>
<td colspan='6'>rushing</td>
<td colspan='5'>receiving</td>
</tr>
<tr>
<td>year</td>
<td>team</td>
<td>att</td>
<td>yds</td>
<td>avg</td>
<td>lng</td>
<td>td</td>
<td>no</td>
<td>yds</td>
<td>... | [
[
"none",
"rushing",
"",
"",
"",
"",
"",
"receiving",
"",
"",
"",
""
],
[
"year",
"team",
"att",
"yds",
"avg",
"lng",
"td",
"no",
"yds",
"avg",
"lng",
"td"
],
[
"1983",
"sf",
"176",
"725",
"4.... | {"title": "national football league statistics", "top_root": {"name": "<TOP>", "value": "<TOP>", "type": "string", "line_idx": null, "children_dict": [{"name": "rushing", "value": "rushing", "type": "string", "children_dict": [{"name": "team", "value": "team", "type": "string", "children_dict": [], "line_idx": 0}, {"na... |
006e304c1c80127c12da2a041702ad17 | 1000 | statcan | 5757 | 1 | a higher proportion of men than women were admitted under the family sponsorship program. | which had a higher proportion of admittances under the family sponsorship program,women or men? | ['men'] | ["pair-argmax"] | {"entity_link": {"top": {"family sponsorship program": {"(0, 4)": "family-sponsored immigrants"}}, "left": {"men": {"(14, 0)": "men"}, "women": {"(3, 0)": "women"}, "[ANSWER]": {"(14, 0)": "men"}}, "top_left_corner": {}}, "quantity_link": {}} | ["=A17"] | {"A17": "(14, 0)"} | <table border='1' cellpadding='4' cellspacing='0'>
<tr>
<td rowspan='3'>country of birth</td>
<td colspan='3'>economic immigrants</td>
<td>family-sponsored immigrants</td>
<td>refugees</td>
<td>other immigrants</td>
<td>total</td>
</tr>
<tr>
<td>principal applicants</td>
<td>second... | [
[
"country of birth",
"economic immigrants",
"",
"",
"family-sponsored immigrants",
"refugees",
"other immigrants",
"total"
],
[
"",
"principal applicants",
"secondary applicants",
"total",
"",
"",
"",
""
],
[
"",
"percent",
"",
... | {"title": "distribution of black immigrants aged 25 to 59, born in the caribbean and bermuda or in latin america, admitted since 1980 at age 25 or older, by admission category, sex and country of birth, canada, 2016", "top_root": {"name": "<TOP>", "value": "<TOP>", "type": "string", "line_idx": null, "children_dict": [... |
96db851bc4d88b027ffa428dea62e748 | 1001 | statcan | 5762 | 1 | for immigrants from some african countries of origin, like cameroon, cote d'ivoire and senegal, more than half of the male immigrants were admitted as a principal applicant under the economic program. | list african countries of origin that have more than half of the male immigrants admitted as a principal applicant under the economic program. | ['cameroon', "cote d'ivoire", 'senegal'] | ["greater_than"] | {"entity_link": {"top": {"admitted as a principal applicant under the economic program": {"(1, 1)": "principal applicants"}}, "left": {"male immigrants": {"(22, 0)": "men"}, "[ANSWER]": {"(33, 0)": "cameroon", "(36, 0)": "cote d'ivoire", "(37, 0)": "senegal"}}, "top_left_corner": {"immigrants from some african countrie... | ["=A36", "= A39", "=A40"] | {"A36": "(33, 0)", "A39": "(36, 0)", "A40": "(37, 0)"} | <table border='1' cellpadding='4' cellspacing='0'>
<tr>
<td rowspan='3'>country of birth</td>
<td colspan='3'>economic immigrants</td>
<td>family-sponsored immigrants</td>
<td>refugees</td>
<td>other immigrants</td>
<td>total</td>
</tr>
<tr>
<td>principal applicants</td>
<td>second... | [
[
"country of birth",
"economic immigrants",
"",
"",
"family-sponsored immigrants",
"refugees",
"other immigrants",
"total"
],
[
"",
"principal applicants",
"secondary applicants",
"total",
"",
"",
"",
""
],
[
"",
"percent",
"",
... | {"title": "distribution of black immigrants aged 25 to 59, born in africa and admitted since 1980 at age 25 or older, by admission category, sex and country of birth, canada, 2016", "top_root": {"name": "<TOP>", "value": "<TOP>", "type": "string", "line_idx": null, "children_dict": [{"name": "economic immigrants", "val... |
46f5c6ff99aa9d0f5d04fd847593fc87 | 1002 | statcan | 5763 | 1 | the black immigrant populations stand out for their prevalence of lone mothers, compared with the rest of the canadian population. | which population has more women aged 25 to 59 who were lone parents? black immigrants or the rest of the canadian population? | ['black population'] | ["pair-argmax"] | {"entity_link": {"top": {}, "left": {"the rest of the canadian population": {"(3, 0)": "rest of the population"}, "[ANSWER]": {"(2, 0)": "black population"}}, "top_left_corner": {}}, "quantity_link": {}} | ["=A5"] | {"A5": "(2, 0)"} | <table border='1' cellpadding='4' cellspacing='0'>
<tr>
<td>2001</td>
<td>2006</td>
<td>2011</td>
<td>2016</td>
</tr>
<tr>
<td>total</td>
<td colspan='4'>percent</td>
</tr>
<tr>
<td>black population</td>
<td>30.7</td>
<td>30.0</td>
<td>29.1</td>
<td>27.4</td>
</tr... | [
[
"",
"2001",
"2006",
"2011",
"2016"
],
[
"total",
"percent",
"",
"",
""
],
[
"black population",
"30.7",
"30.0",
"29.1",
"27.4"
],
[
"rest of the population",
"10.1",
"10.2",
"10.4",
"10.6"
],
[
"immigrant women",
... | {"title": "percentage of women aged 25 to 59 who were lone parents, by region of origin of the immigrant and canadian-born populations, 2001 to 2016", "top_root": {"name": "<TOP>", "value": "<TOP>", "type": "string", "line_idx": null, "children_dict": [{"name": "2001", "value": "2001", "type": "string", "children_dict"... |
ea1e8a9b80bbc4bc75089edece4613ab | 1002 | statcan | 5764 | 1 | among black immigrant women aged 25 to 59 in 2016, about three in ten were lone parents. | how many percent of black immigrant women aged 25 to 59 in 2016 were lone parents? | [29.2] | ["none"] | {"entity_link": {"top": {"in 2016": {"(0, 4)": 2016.0}}, "left": {"black immigrant women aged 25 to 59": {"(5, 0)": "black population"}}, "top_left_corner": {}}, "quantity_link": {"[ANSWER]": {"(6, 4)": 29.2}}} | ["=E9"] | {"E9": "(6, 4)"} | <table border='1' cellpadding='4' cellspacing='0'>
<tr>
<td>2001</td>
<td>2006</td>
<td>2011</td>
<td>2016</td>
</tr>
<tr>
<td>total</td>
<td colspan='4'>percent</td>
</tr>
<tr>
<td>black population</td>
<td>30.7</td>
<td>30.0</td>
<td>29.1</td>
<td>27.4</td>
</tr... | [
[
"",
"2001",
"2006",
"2011",
"2016"
],
[
"total",
"percent",
"",
"",
""
],
[
"black population",
"30.7",
"30.0",
"29.1",
"27.4"
],
[
"rest of the population",
"10.1",
"10.2",
"10.4",
"10.6"
],
[
"immigrant women",
... | {"title": "percentage of women aged 25 to 59 who were lone parents, by region of origin of the immigrant and canadian-born populations, 2001 to 2016", "top_root": {"name": "<TOP>", "value": "<TOP>", "type": "string", "line_idx": null, "children_dict": [{"name": "2001", "value": "2001", "type": "string", "children_dict"... |
7a669cbe702769e1b9b5facc0244f24b | 1002 | statcan | 5765 | 1 | among black immigrant women aged 25 to 59 in 2016, one in ten for other immigrant women were lone parents. | among black immigrant women aged 25 to 59 in 2016, how many percent of other immigrant women were lone parents? | [9.8] | ["none"] | {"entity_link": {"top": {"in 2016": {"(0, 4)": 2016.0}}, "left": {"black immigrant women aged 25 to 59": {"(5, 0)": "black population"}, "other immigrant women": {"(10, 0)": "rest of the population"}}, "top_left_corner": {}}, "quantity_link": {"[ANSWER]": {"(10, 4)": 9.8}}} | ["=E13"] | {"E13": "(10, 4)"} | <table border='1' cellpadding='4' cellspacing='0'>
<tr>
<td>2001</td>
<td>2006</td>
<td>2011</td>
<td>2016</td>
</tr>
<tr>
<td>total</td>
<td colspan='4'>percent</td>
</tr>
<tr>
<td>black population</td>
<td>30.7</td>
<td>30.0</td>
<td>29.1</td>
<td>27.4</td>
</tr... | [
[
"",
"2001",
"2006",
"2011",
"2016"
],
[
"total",
"percent",
"",
"",
""
],
[
"black population",
"30.7",
"30.0",
"29.1",
"27.4"
],
[
"rest of the population",
"10.1",
"10.2",
"10.4",
"10.6"
],
[
"immigrant women",
... | {"title": "percentage of women aged 25 to 59 who were lone parents, by region of origin of the immigrant and canadian-born populations, 2001 to 2016", "top_root": {"name": "<TOP>", "value": "<TOP>", "type": "string", "line_idx": null, "children_dict": [{"name": "2001", "value": "2001", "type": "string", "children_dict"... |
a39496f71bad9ca3352cf1cfee049e97 | 1002 | statcan | 5766 | 1 | the highest proportion of lone mothers was found in women from caribbean and latin-american countries among black immigrant women aged 25 to 59 in 2016. | which region of origion of the immigrants has the highest proportion of lone mothers among black immigrant women aged 25 to 59 in 2016? | ['caribbean and latin america'] | ["argmax"] | {"entity_link": {"top": {"in 2016": {"(0, 4)": 2016.0}}, "left": {"black immigrant women aged 25 to 59": {"(5, 0)": "black population"}, "[ANSWER]": {"(7, 0)": "caribbean and latin america"}, "proportion": {"(1, 1)": "percent"}}, "top_left_corner": {}}, "quantity_link": {}} | ["=A10"] | {"A10": "(7, 0)"} | <table border='1' cellpadding='4' cellspacing='0'>
<tr>
<td>2001</td>
<td>2006</td>
<td>2011</td>
<td>2016</td>
</tr>
<tr>
<td>total</td>
<td colspan='4'>percent</td>
</tr>
<tr>
<td>black population</td>
<td>30.7</td>
<td>30.0</td>
<td>29.1</td>
<td>27.4</td>
</tr... | [
[
"",
"2001",
"2006",
"2011",
"2016"
],
[
"total",
"percent",
"",
"",
""
],
[
"black population",
"30.7",
"30.0",
"29.1",
"27.4"
],
[
"rest of the population",
"10.1",
"10.2",
"10.4",
"10.6"
],
[
"immigrant women",
... | {"title": "percentage of women aged 25 to 59 who were lone parents, by region of origin of the immigrant and canadian-born populations, 2001 to 2016", "top_root": {"name": "<TOP>", "value": "<TOP>", "type": "string", "line_idx": null, "children_dict": [{"name": "2001", "value": "2001", "type": "string", "children_dict"... |
41c09839ad631914ee8fb625dd81bc05 | 1003 | statcan | 5773 | 1 | the proportions of black male immigrants from the caribbean and latin america with a postsecondary diploma or a university diploma were lower than those of black male immigrants from africa. | which region of birth has fewer proportion of black male immigrants with a postsecondary diploma or a university diploma? black male immigrants from africa or from caribbean and latin america? | ['caribbean and latin america'] | ["pair-argmin"] | {"entity_link": {"top": {"black male immigrants": {"(0, 3)": "men"}, "with a postsecondary diploma or a university diploma": {"(1, 3)": "non-university or university postsecondary diploma"}}, "left": {"from africa": {"(4, 0)": "africa"}, "[ANSWER]": {"(3, 0)": "caribbean and latin america"}, "proportions": {"(2, 1)": "... | ["=A6"] | {"A6": "(3, 0)"} | <table border='1' cellpadding='4' cellspacing='0'>
<tr>
<td rowspan='2'>region or country of birth</td>
<td colspan='2'>women</td>
<td colspan='2'>men</td>
</tr>
<tr>
<td>non-university or university postsecondary diploma</td>
<td>university degree only</td>
<td>non-university or universit... | [
[
"region or country of birth",
"women",
"",
"men",
""
],
[
"",
"non-university or university postsecondary diploma",
"university degree only",
"non-university or university postsecondary diploma",
"university degree only"
],
[
"region of birth",
"percent",
... | {"title": "percentage of black immigrants aged 25 to 59 with a postsecondary diploma, by sex and region or country of birth, canada, 2016", "top_root": {"name": "<TOP>", "value": "<TOP>", "type": "string", "line_idx": null, "children_dict": [{"name": "women", "value": "women", "type": "string", "children_dict": [{"name... |
8fb0e0a6818fcfa37daab4e055b84f53 | 1003 | statcan | 5774 | 1 | the proportion holding a postsecondary diploma for women born in the caribbean or latin america in 2016 was slightly higher than those born in africa. | which region of birth has higher proportion of black female immigrants with a postsecondary diploma or a university diploma? black female immigrants from africa or from caribbean and latin america? | ['caribbean and latin america'] | ["pair-argmax"] | {"entity_link": {"top": {"women": {"(0, 1)": "women"}, "holding a postsecondary diploma": {"(1, 1)": "non-university or university postsecondary diploma"}}, "left": {"those born in africa": {"(4, 0)": "africa"}, "[ANSWER]": {"(3, 0)": "caribbean and latin america"}, "proportion": {"(2, 1)": "percent"}}, "top_left_corne... | ["=A6"] | {"A6": "(3, 0)"} | <table border='1' cellpadding='4' cellspacing='0'>
<tr>
<td rowspan='2'>region or country of birth</td>
<td colspan='2'>women</td>
<td colspan='2'>men</td>
</tr>
<tr>
<td>non-university or university postsecondary diploma</td>
<td>university degree only</td>
<td>non-university or universit... | [
[
"region or country of birth",
"women",
"",
"men",
""
],
[
"",
"non-university or university postsecondary diploma",
"university degree only",
"non-university or university postsecondary diploma",
"university degree only"
],
[
"region of birth",
"percent",
... | {"title": "percentage of black immigrants aged 25 to 59 with a postsecondary diploma, by sex and region or country of birth, canada, 2016", "top_root": {"name": "<TOP>", "value": "<TOP>", "type": "string", "line_idx": null, "children_dict": [{"name": "women", "value": "women", "type": "string", "children_dict": [{"name... |
88d1459e99dabcc8efddd55b087dd2a6 | 1005 | statcan | 5783 | 1 | among black immigrant women, the employment rate was higher for women born in the caribbean or in latin america than for women born in africa. | among black immigrant women, which region of birth has a higher the employment rate? women born in the caribbean or in latin america tor women born in africa? | ['caribbean and latin america'] | ["pair-argmax"] | {"entity_link": {"top": {"black immigrant women": {"(0, 1)": "women"}, "the employment rate": {"(1, 1)": "employment rate"}}, "left": {"in africa": {"(4, 0)": "africa"}, "[ANSWER]": {"(3, 0)": "caribbean and latin america"}}, "top_left_corner": {}}, "quantity_link": {}} | ["=A6"] | {"A6": "(3, 0)"} | <table border='1' cellpadding='4' cellspacing='0'>
<tr>
<td rowspan='2'>region or country of birth</td>
<td colspan='2'>women</td>
<td colspan='2'>men</td>
</tr>
<tr>
<td>employment rate</td>
<td>unemployment rate</td>
<td>employment rate</td>
<td>unemployment rate</td>
</tr>
<tr>
... | [
[
"region or country of birth",
"women",
"",
"men",
""
],
[
"",
"employment rate",
"unemployment rate",
"employment rate",
"unemployment rate"
],
[
"region of birth",
"percent",
"",
"",
""
],
[
"caribbean and latin america",
"76.1",
... | {"title": "employment and unemployment rates (expressed as percentages) of black immigrant populations aged 25 to 59, by sex and country of birth, canada, 2016", "top_root": {"name": "<TOP>", "value": "<TOP>", "type": "string", "line_idx": null, "children_dict": [{"name": "women", "value": "women", "type": "string", "c... |
5a4282c6be891490fcc018c2cba63deb | 1005 | statcan | 5785 | 1 | among women, immigrants from somalia, sudan, the democratic republic of the congo and nigeria had the lowest employment rates. | which top 4 countries of birth had the lowest the lowest employment rates? | ['democratic republic of the congo', 'nigeria', 'somalia', 'sudan'] | ["topk-argmin"] | {"entity_link": {"top": {"women": {"(0, 1)": "women"}, "employment rates": {"(1, 1)": "employment rate"}}, "left": {"[ANSWER]": {"(26, 0)": "democratic republic of the congo", "(28, 0)": "nigeria", "(18, 0)": "somalia", "(20, 0)": "sudan"}}, "top_left_corner": {}}, "quantity_link": {}} | ["=A29", "=A31", "=A21", "=A23"] | {"A29": "(26, 0)", "A31": "(28, 0)", "A21": "(18, 0)", "A23": "(20, 0)"} | <table border='1' cellpadding='4' cellspacing='0'>
<tr>
<td rowspan='2'>region or country of birth</td>
<td colspan='2'>women</td>
<td colspan='2'>men</td>
</tr>
<tr>
<td>employment rate</td>
<td>unemployment rate</td>
<td>employment rate</td>
<td>unemployment rate</td>
</tr>
<tr>
... | [
[
"region or country of birth",
"women",
"",
"men",
""
],
[
"",
"employment rate",
"unemployment rate",
"employment rate",
"unemployment rate"
],
[
"region of birth",
"percent",
"",
"",
""
],
[
"caribbean and latin america",
"76.1",
... | {"title": "employment and unemployment rates (expressed as percentages) of black immigrant populations aged 25 to 59, by sex and country of birth, canada, 2016", "top_root": {"name": "<TOP>", "value": "<TOP>", "type": "string", "line_idx": null, "children_dict": [{"name": "women", "value": "women", "type": "string", "c... |
d197945e0b0a3e7db1face7153fa0e1a | 1006 | statcan | 5791 | 1 | unemployment was higher d for women whose region of ancestry was africa than those in caribbean and latin america. | which region of ancestry has a higher uunemployment? women whose region of ancestry was africa or those in caribbean and latin america? | ['women'] | ["pair-argmax"] | {"entity_link": {"top": {"unemployment": {"(1, 2)": "unemployment rate"}, "[ANSWER]": {"(0, 1)": "women"}}, "left": {"africa": {"(5, 0)": "africa"}, "in caribbean and latin america": {"(4, 0)": "caribbean and latin america"}}, "top_left_corner": {"region of ancestry": {"(0, 0)": "region or country of ancestry"}}}, "qua... | ["=B3"] | {"B3": "(0, 1)"} | <table border='1' cellpadding='4' cellspacing='0'>
<tr>
<td rowspan='3'>region or country of ancestry</td>
<td colspan='2'>women</td>
<td colspan='2'>men</td>
</tr>
<tr>
<td>employment rate</td>
<td>unemployment rate</td>
<td>employment rate</td>
<td>unemployment rate</td>
</tr>
<t... | [
[
"region or country of ancestry",
"women",
"",
"men",
""
],
[
"",
"employment rate",
"unemployment rate",
"employment rate",
"unemployment rate"
],
[
"",
"percent",
"",
"",
""
],
[
"region of ancestry",
"",
"",
"",
""
],
... | {"title": "employment and unemployment rates (expressed as percentages) of the canadian-born black population aged 25 to 59, by sex and country of ancestry, 2016", "top_root": {"name": "<TOP>", "value": "<TOP>", "type": "string", "line_idx": null, "children_dict": [{"name": "women", "value": "women", "type": "string", ... |
2c4b9acc4e415d3b25bc80c695925abb | 1007 | statcan | 5792 | 1 | black female workers were mostly concentrated in the health care and social assistance sector. | which sector has the most black female workers? | ['health care and social assistance'] | ["argmax"] | {"entity_link": {"top": {"black female workers": {"(0, 1)": "black female workers"}}, "left": {"[ANSWER]": {"(17, 0)": "health care and social assistance"}}, "top_left_corner": {"sector": {"(0, 0)": "sector"}}}, "quantity_link": {}} | ["=A20"] | {"A20": "(17, 0)"} | <table border='1' cellpadding='4' cellspacing='0'>
<tr>
<td rowspan='3'>sector</td>
<td colspan='4'>black female workers</td>
<td colspan='4'>other female workers</td>
</tr>
<tr>
<td>immigrant</td>
<td>second generation</td>
<td>third generation or more</td>
<td>total</td>
<td>immi... | [
[
"sector",
"black female workers",
"",
"",
"",
"other female workers",
"",
"",
""
],
[
"",
"immigrant",
"second generation",
"third generation or more",
"total",
"immigrant",
"second generation",
"third generation or more",
"total"
],
... | {"title": "percentage distribution of black female workers and other female workers aged 25 to 59, by industry sector and generation, canada, 2016", "top_root": {"name": "<TOP>", "value": "<TOP>", "type": "string", "line_idx": null, "children_dict": [{"name": "black female workers", "value": "black female workers", "ty... |
a26ae67eff821dd8815180d2473d1f3a | 1007 | statcan | 5792 | 2 | black female workers in the health care and social assistance sector are 12 percentage points higher than the rest of the employed female population. | which sector has the most black female workers? | [11.7] | ["diff"] | {"entity_link": {"top": {"black female workers": {"(0, 1)": "black female workers"}, "the rest of the employed female population": {"(0, 5)": "other female workers"}}, "left": {"health care and social assistance sector": {"(17, 0)": "health care and social assistance"}}, "top_left_corner": {}}, "quantity_link": {"[ANSW... | ["=E20-I20"] | {"E20": "(17, 4)", "I20": "(17, 8)"} | <table border='1' cellpadding='4' cellspacing='0'>
<tr>
<td rowspan='3'>sector</td>
<td colspan='4'>black female workers</td>
<td colspan='4'>other female workers</td>
</tr>
<tr>
<td>immigrant</td>
<td>second generation</td>
<td>third generation or more</td>
<td>total</td>
<td>immi... | [
[
"sector",
"black female workers",
"",
"",
"",
"other female workers",
"",
"",
""
],
[
"",
"immigrant",
"second generation",
"third generation or more",
"total",
"immigrant",
"second generation",
"third generation or more",
"total"
],
... | {"title": "percentage distribution of black female workers and other female workers aged 25 to 59, by industry sector and generation, canada, 2016", "top_root": {"name": "<TOP>", "value": "<TOP>", "type": "string", "line_idx": null, "children_dict": [{"name": "black female workers", "value": "black female workers", "ty... |
End of preview. Expand in Data Studio
- Downloads last month
- 28