{"columns":[{"alerts":[],"column":"fips","extras":{"histogram":{"counts":[97,15,133,64,12,68,159,49,194,204,184,39,33,152,197,149,27,54,162,141,113,67,51,161,283,48,99,94,95,0,5,0,0,1,0,4,78,0,0,3],"edges":[1001.0,2926.725,4852.45,6778.174999999999,8703.9,10629.625,12555.349999999999,14481.074999999999,16406.8,18332.524999999998,20258.25,22183.975,24109.699999999997,26035.425,27961.149999999998,29886.875,31812.6,33738.325,35664.049999999996,37589.775,39515.5,41441.225,43366.95,45292.674999999996,47218.399999999994,49144.125,51069.85,52995.575,54921.299999999996,56847.024999999994,58772.75,60698.475,62624.2,64549.924999999996,66475.65,68401.375,70327.09999999999,72252.825,74178.55,76104.275,78030.0]},"sample":[8067.0,12071.0,26103.0,21101.0,23015.0,2170.0,25013.0,1055.0,30031.0,35041.0,40013.0,42049.0,47163.0,48205.0,54107.0,53071.0,54031.0,13319.0,18051.0,21197.0,23007.0,30033.0,31075.0,38007.0,42035.0,42099.0,47041.0,47117.0,48373.0,48005.0,48441.0,48055.0,48063.0,48223.0,48313.0,51019.0,53005.0,54085.0,54017.0,72031.0,12017.0,12131.0,5073.0,5107.0,5093.0,6093.0,39095.0,41025.0,42055.0,16069.0,16021.0,18129.0,19111.0,8037.0,36115.0,36009.0,22017.0,23031.0,23003.0,27027.0,27119.0,1063.0,29197.0,30053.0,30005.0,35045.0,36019.0,37129.0,37089.0,38017.0,13283.0,13265.0,16037.0,18175.0,20149.0,20055.0,20167.0,47079.0,47147.0,48409.0,51093.0,51059.0,53033.0,54047.0,4007.0,5117.0,6047.0,6043.0,8033.0,12007.0,48001.0,21051.0,28081.0,28073.0,30049.0,31167.0,32015.0,37111.0,47049.0,47119.0,24033.0,26083.0,27167.0,28021.0,39061.0,40079.0,49045.0,53019.0,55051.0,51660.0,51097.0,54045.0,1129.0,6007.0,13073.0,18147.0,26121.0,40125.0,8049.0,22125.0,2158.0,21059.0,19021.0,21189.0,27015.0,31171.0,41013.0,42091.0,45067.0,48115.0,48025.0,51041.0,53037.0,60040.0,69100.0,72023.0,5009.0,6085.0,40089.0,42111.0,42101.0,45049.0,47187.0,48289.0,54087.0,56013.0,6053.0,26029.0,36081.0,1117.0,22105.0,24035.0,28109.0,28103.0,37039.0,13025.0,19179.0,48057.0,51159.0,51069.0,48349.0,12009.0,4027.0,2282.0,27021.0,48053.0,51111.0,25007.0,16085.0,21179.0,48239.0,48381.0,51047.0,6057.0,17165.0,26109.0,16005.0,42023.0,48189.0,13181.0,22083.0,35021.0,72015.0,11001.0,42103.0,34013.0,17027.0,48061.0,13221.0,54103.0,46075.0,47089.0,28033.0,56007.0,29019.0,49055.0,42089.0,51199.0,53029.0,5075.0,26035.0,26007.0,27163.0,29069.0,12109.0,37051.0,38055.0,6009.0,51175.0,48155.0,9190.0,37103.0,13031.0,6095.0,17001.0,16075.0,19097.0,17059.0,26051.0,18135.0,36029.0,26085.0,21023.0,40035.0,20077.0,20043.0,20005.0,28095.0,2068.0,26017.0,41067.0,39135.0,72021.0,12059.0,46073.0,35005.0,48049.0,4003.0,48207.0,4011.0,37035.0,48101.0,48193.0,72139.0,37107.0,48107.0,72153.0,38015.0,50015.0,72001.0,8103.0,8075.0,51750.0,39145.0,51620.0,53001.0,40091.0,18181.0,18121.0,18037.0,31003.0,21215.0,55105.0,21149.0,38095.0,55031.0,40033.0,26143.0,27153.0,20031.0,20165.0,29119.0,29077.0,46007.0,46031.0,29135.0,48079.0,13259.0,18149.0,5123.0,8125.0,27019.0,19093.0,48495.0,8073.0,27009.0,19137.0,13017.0,38011.0,38023.0,20015.0,20085.0,51650.0,48255.0,48297.0,48191.0,48269.0,13249.0,20061.0,13165.0,20199.0,20101.0,54069.0,46053.0,23011.0,17169.0,18103.0,46102.0,55061.0,55065.0,27141.0,18005.0,24045.0,18113.0,19191.0,26031.0,17145.0,26009.0,37045.0,17123.0,17101.0,20019.0,37179.0,36055.0,28057.0,37077.0,8041.0,29155.0,34039.0,26069.0,29147.0,19155.0,19005.0,42085.0,40009.0,26131.0,19101.0,19123.0,55053.0,19059.0,20153.0,20179.0,36083.0,55091.0,20035.0,20089.0,47111.0,5149.0,5087.0,40017.0,55101.0,55125.0,56023.0,4019.0,51680.0,5143.0,6067.0,13243.0,51760.0,44003.0,17167.0,13083.0,18165.0,51079.0,20191.0,20037.0,18133.0,19047.0,26091.0,20021.0,54097.0,55005.0,46071.0,47169.0,29043.0,39023.0,47015.0,36101.0,47115.0,48017.0,48257.0,51735.0,30065.0,31045.0,31123.0,48143.0,25023.0,1057.0,41041.0,28067.0,28125.0,36109.0,31177.0,32013.0,36121.0,28037.0,46107.0,17033.0,19087.0,47087.0,21113.0,47047.0,72117.0,32007.0,22011.0,19159.0,26127.0,20117.0,28141.0,37049.0,18053.0,19121.0,36011.0,20083.0,37171.0,48045.0,37025.0,72149.0,72049.0,13045.0,48497.0,48251.0,48059.0,48281.0,48305.0,36099.0,37001.0,51109.0,29161.0,72033.0,51021.0,51580.0,31009.0,37081.0,38045.0,38039.0,22095.0,40103.0,42079.0,28077.0,45039.0,72035.0,13307.0,47077.0,72091.0,40111.0,31105.0,37143.0,31169.0,51510.0,35027.0,37157.0,47071.0,47083.0,21163.0,31073.0,39163.0,29181.0,37189.0,13159.0,42121.0,1113.0,37149.0,54075.0,55113.0,17111.0,21117.0,17187.0,13281.0,16009.0,19193.0,47139.0,29015.0,37135.0,38091.0,38029.0,1059.0,5127.0,42109.0,48345.0,55073.0,48047.0,20007.0,18137.0,18139.0,19015.0,31127.0,29215.0,39105.0,5043.0,13117.0,27037.0,47179.0,27149.0,28127.0,31069.0,13097.0,28155.0,39143.0,21211.0]},"kind":"numeric","n":3235,"n_null":0,"n_unique":3235,"null_rate":0.0,"stats":{"iqr":27090.0,"kurtosis":-0.6075295996326879,"max":78030.0,"mean":31522.78145285935,"median":30035.0,"min":1001.0,"n_outliers":0,"outlier_rate":0.0,"q1":19036.0,"q3":46126.0,"skew":0.17380362219410941,"std":16431.82411643927,"zero_rate":0.0}},{"alerts":[{"code":"short_text","level":"info","message":"95th-percentile length under 20 chars"},{"code":"duplicates","level":"warn","message":"39.0% duplicate strings"}],"column":"county_name","extras":{"language_counts":{},"language_sample_size":3235,"length_histogram":{"counts":[1,0,0,0,0,29,256,465,683,588,495,294,221,67,51,23,16,14,8,4,7,1,1,1,0,2,1,1,1,1,0,0,0,0,2,1,0,0,0,1],"edges":[4.0,5.05,6.1,7.15,8.2,9.25,10.3,11.350000000000001,12.4,13.450000000000001,14.5,15.55,16.6,17.65,18.700000000000003,19.75,20.8,21.85,22.900000000000002,23.95,25.0,26.05,27.1,28.150000000000002,29.200000000000003,30.25,31.3,32.35,33.400000000000006,34.45,35.5,36.550000000000004,37.6,38.65,39.7,40.75,41.800000000000004,42.85,43.9,44.95,46.0]},"near_unique":false,"sample":["Pickens County","Knox County","Alpine County","Ozaukee County","Keokuk County","Rush County","DeKalb County","Butler County","Dewey County","Hartley County","Duval County","Casey County","Glasscock County","Cass County","Pawnee County","Clay County","New Castle County","Madison County","Webster County","Rains County","Tangipahoa Parish","Copper River Census Area","Wise County","Mohave County","Monongalia County","Wabasha County","Wallowa County","Missoula County","Marshall County","Mississippi County","Ocean County","Woods County","Harrison County","Burke County","Wharton County","Montgomery County","Winnebago County","Taylor County","Erie County","Oconto County","Adams County","Bastrop County","Kanawha County","Yabucoa Municipio","Snyder County","Maries County","Bucks County","Brazoria County","King County","Fajardo Municipio"],"top_values":[["Washington County",30],["Jefferson County",25],["Franklin County",24],["Lincoln County",23],["Jackson County",23],["Madison County",19],["Montgomery County",18],["Clay County",18],["Union County",17],["Marion County",17],["Monroe County",17],["Wayne County",16],["Warren County",14],["Greene County",14],["Grant County",14],["Carroll County",13],["Lee County",12],["Douglas County",12],["Marshall County",12],["Lake County",12]],"top_words":[["county",2999],["municipio",78],["parish",64],["city",47],["washington",31],["st.",29],["jefferson",28],["franklin",26],["lincoln",24],["jackson",24],["san",21],["madison",20],["union",18],["montgomery",18],["lake",18],["clay",18],["borough",17],["marion",17],["monroe",17],["wayne",16],["grant",15],["carroll",15],["warren",14],["greene",14],["clark",13]],"vocab_skipped":null,"word_histogram":{"counts":[1,0,0,0,0,0,2995,0,0,0,0,0,211,0,0,0,0,0,23,0,0,0,0,0,4,0,0,0,0,1],"edges":[1.0,1.1666666666666667,1.3333333333333333,1.5,1.6666666666666665,1.8333333333333333,2.0,2.1666666666666665,2.333333333333333,2.5,2.6666666666666665,2.833333333333333,3.0,3.1666666666666665,3.333333333333333,3.5,3.6666666666666665,3.833333333333333,4.0,4.166666666666666,4.333333333333333,4.5,4.666666666666666,4.833333333333333,5.0,5.166666666666666,5.333333333333333,5.5,5.666666666666666,5.833333333333333,6.0]}},"kind":"text","n":3235,"n_null":0,"n_unique":1973,"null_rate":0.0,"stats":{"allcaps_rate":0.0,"boilerplate_rate":0.0,"duplicate_rate":0.3901081916537867,"emoji_rate":0.0,"len_max":46,"len_mean":14.179289026275116,"len_median":14.0,"len_min":4,"len_p95":18.0,"n_duplicates":1262,"n_empty":0,"one_word_rate":0.0003091190108191654,"readability_flesch_mean":33.650475000000014,"url_rate":0.0,"vocab_size":1973,"word_mean":2.084080370942813,"word_median":2.0}},{"alerts":[],"column":"state","extras":{"singletons":2,"top_values":[["TX",254],["GA",159],["VA",133],["KY",120],["MO",115],["KS",105],["IL",102],["NC",100],["IA",99],["TN",95],["NE",93],["IN",92],["OH",88],["MN",87],["MI",83],["MS",82],["PR",78],["OK",77],["AR",75],["WI",72]]},"kind":"categorical","n":3235,"n_null":0,"n_unique":56,"null_rate":0.0,"stats":{"cardinality":56,"entropy":5.3378417787675385,"entropy_ratio":0.9191519806191367,"top_rate":0.078516228748068,"top_value":"TX"}},{"alerts":[],"column":"state_name","extras":{"singletons":2,"top_values":[["Texas",254],["Georgia",159],["Virginia",133],["Kentucky",120],["Missouri",115],["Kansas",105],["Illinois",102],["North Carolina",100],["Iowa",99],["Tennessee",95],["Nebraska",93],["Indiana",92],["Ohio",88],["Minnesota",87],["Michigan",83],["Mississippi",82],["Puerto Rico",78],["Oklahoma",77],["Arkansas",75],["Wisconsin",72]]},"kind":"categorical","n":3235,"n_null":0,"n_unique":56,"null_rate":0.0,"stats":{"cardinality":56,"entropy":5.3378417787675385,"entropy_ratio":0.9191519806191367,"top_rate":0.078516228748068,"top_value":"Texas"}},{"alerts":[{"code":"high_skew","level":"info","message":"skew=+7.51"}],"column":"distance_to_deposit","extras":{"histogram":{"counts":[1519,1181,343,64,4,2,4,2,0,3,8,82,3,3,1,0,0,5,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,2,0,0,0,2,3],"edges":[1.8,143.065,284.33,425.59499999999997,566.8599999999999,708.1249999999999,849.3899999999999,990.6549999999999,1131.9199999999998,1273.1849999999997,1414.4499999999998,1555.715,1696.9799999999998,1838.2449999999997,1979.5099999999998,2120.775,2262.04,2403.305,2544.5699999999997,2685.835,2827.1,2968.365,3109.63,3250.895,3392.16,3533.4249999999997,3674.6899999999996,3815.955,3957.22,4098.485,4239.75,4381.014999999999,4522.28,4663.545,4804.8099999999995,4946.075,5087.339999999999,5228.605,5369.87,5511.134999999999,5652.4]},"sample":[30.7,457.1,486.7,122.4,163.6,1493.3,64.5,47.1,68.4,89.3,117.8,48.2,160.4,121.7,68.7,115.1,171.8,169.7,88.1,94.7,161.5,215.8,207.5,78.4,91.8,115.3,188.1,155.8,239.5,202.5,145.3,147.9,94.3,106.2,241.1,196.0,129.8,85.4,101.8,1613.3,365.7,186.7,68.3,114.0,103.1,45.9,115.0,94.4,139.9,84.9,9.4,118.1,131.1,23.0,54.5,24.8,119.7,80.7,133.9,290.0,312.1,115.1,124.4,71.9,196.6,65.9,34.9,406.6,238.6,283.2,206.8,182.3,62.8,84.4,162.8,232.1,277.3,195.6,212.5,154.3,270.1,167.7,165.6,109.6,61.8,68.6,61.5,11.5,11.9,322.7,188.0,128.4,171.3,136.7,37.0,300.6,125.3,212.6,211.2,170.8,152.8,543.3,288.7,230.6,103.7,69.4,9.4,21.7,498.1,202.0,220.6,77.1,152.5,45.7,216.0,107.1,263.6,165.6,43.3,194.9,1984.6,122.4,299.6,110.2,399.2,266.4,81.8,35.2,376.6,50.7,120.7,258.4,139.6,4698.8,5582.9,1568.6,81.7,94.3,43.7,108.1,41.0,281.8,183.8,218.8,72.4,126.7,116.4,388.6,69.0,36.6,131.0,131.0,116.8,150.2,175.7,274.4,160.9,174.9,202.4,178.6,187.9,461.1,22.6,1130.7,407.2,178.7,270.1,51.4,51.2,151.3,185.6,152.0,208.2,5.4,110.4,410.2,58.9,79.5,139.9,209.3,185.9,67.6,1626.4,155.1,54.0,47.4,41.7,213.0,175.2,84.4,169.6,193.3,113.6,124.4,14.6,65.3,31.2,244.2,201.2,43.2,284.2,276.2,431.7,98.4,356.2,333.0,125.6,34.1,287.4,199.1,99.8,394.6,254.5,61.8,91.0,31.3,249.5,129.7,272.3,117.0,38.4,315.6,79.2,50.2,209.2,115.0,106.8,143.3,1596.6,234.2,44.2,126.7,1604.1,171.4,229.4,109.9,202.7,61.6,168.2,86.5,231.4,186.4,243.7,1613.6,369.6,121.5,1583.0,117.3,48.2,1585.4,64.6,110.4,161.3,16.2,287.9,75.8,113.9,83.0,22.1,80.5,340.5,142.5,241.8,140.8,252.1,506.6,241.2,294.2,373.3,116.2,293.8,20.8,53.6,186.6,91.6,23.0,101.4,105.4,122.1,71.9,138.7,424.6,283.8,28.3,101.7,407.7,186.7,194.7,20.1,201.6,149.9,131.4,257.6,113.1,97.0,188.9,161.3,120.4,178.0,238.1,192.2,249.2,55.6,249.6,185.3,104.3,98.4,159.1,343.0,269.8,423.7,70.4,158.0,152.2,311.1,347.0,66.5,348.4,243.7,158.6,66.0,108.2,282.4,19.3,151.0,281.9,74.2,120.3,41.8,260.1,141.3,222.8,316.2,29.0,267.0,509.3,159.6,184.2,381.3,338.3,216.9,254.8,100.2,401.0,142.4,263.8,217.4,81.1,72.6,227.5,223.4,459.4,34.5,65.4,208.9,61.0,39.2,132.9,247.0,21.7,90.9,110.8,28.8,219.9,177.4,47.8,17.7,254.1,164.6,32.4,129.0,458.3,155.4,214.8,56.2,98.1,174.8,17.3,132.4,121.9,168.0,248.6,193.4,192.4,151.2,240.7,38.3,98.6,72.9,166.7,214.1,22.2,243.7,162.0,16.3,197.4,130.0,47.1,154.4,213.3,126.1,134.7,1552.8,184.1,249.8,149.3,285.6,179.0,164.1,394.5,100.9,187.3,43.5,274.1,198.5,175.1,259.7,1600.2,1648.2,62.1,213.5,232.4,175.5,200.0,75.5,24.1,262.7,245.4,58.9,1601.2,141.3,159.7,294.5,243.5,195.1,232.9,119.0,156.7,57.5,172.3,293.3,1616.9,117.0,189.0,1584.1,129.2,94.1,313.1,241.6,161.1,109.9,227.1,184.4,212.2,113.1,284.9,31.8,78.3,182.4,130.4,59.7,88.5,244.4,151.6,482.4,207.1,101.0,153.7,172.3,29.4,298.3,154.6,26.4,270.4,254.6,110.1,133.2,48.0,101.0,159.3,397.9,122.4,238.9,103.9,85.5,235.0,169.2,99.1,40.1,139.9,129.2,413.1,170.0,318.0,198.8,173.1,79.2,185.0,102.2,133.7]},"kind":"numeric","n":3235,"n_null":0,"n_unique":2202,"null_rate":0.0,"stats":{"iqr":150.25,"kurtosis":77.60100355588999,"max":5652.4,"mean":230.12024729520866,"median":152.0,"min":1.8,"n_outliers":159,"outlier_rate":0.0491499227202473,"q1":85.5,"q3":235.75,"skew":7.510814821363708,"std":399.8537989401132,"zero_rate":0.0}},{"alerts":[],"column":"nearest_deposit","extras":{"singletons":10,"top_values":[["Hatchet Creek Copper",434],["Chaney No 1 Clay Mine",302],["Cardonia Pit",263],["Hager Mine",179],["Lodgepole Quad",171],["Cooper Mine",164],["Stewart May",161],["Main Pass Sulfur Mine",115],["Dunn Bank",101],["Batesville District",96],["Unknown - Coal & Zn",90],["Tole and Thorp Fireclay Mine",89],["Ventech Gas Processors Sulfur Plant",84],["Midland Farms Sulfur Plant",66],["Belden Pit",65],["Afc Pit",45],["Iron Mine Hill Deposit",43],["Butte Valley, Alamo #1",42],["Santa Rosa Tar Sands",41],["Old Leyden Mine",39]]},"kind":"categorical","n":3235,"n_null":0,"n_unique":97,"null_rate":0.0,"stats":{"cardinality":97,"entropy":4.999036059896777,"entropy_ratio":0.7574397085886606,"top_rate":0.13415765069551777,"top_value":"Hatchet Creek Copper"}},{"alerts":[],"column":"deposit_type","extras":{"singletons":0,"top_values":[["Coal",1345],["Copper",485],["Iron",403],["Oil",400],["Natural Gas",235],["Lead",170],["Phosphate",81],["Gold",72],["Zinc",23],["Silver",21]]},"kind":"categorical","n":3235,"n_null":0,"n_unique":10,"null_rate":0.0,"stats":{"cardinality":10,"entropy":2.5355361489845682,"entropy_ratio":0.7632724359346922,"top_rate":0.41576506955177744,"top_value":"Coal"}},{"alerts":[],"column":"deposit_era","extras":{"singletons":0,"top_values":[["Pennsylvanian",732],["Devonian",422],["Paleozoic",419],["Tertiary",401],["Mississippian",401],["Precambrian",327],["Cretaceous",289],["Miocene",149],["Permian",95]]},"kind":"categorical","n":3235,"n_null":0,"n_unique":9,"null_rate":0.0,"stats":{"cardinality":9,"entropy":2.9965791716816943,"entropy_ratio":0.9453154791732468,"top_rate":0.22627511591962907,"top_value":"Pennsylvanian"}},{"alerts":[],"column":"deposit_state","extras":{"singletons":0,"top_values":[["Missouri",478],["Ohio",448],["Alabama",434],["Indiana",263],["Arkansas",257],["South Dakota",210],["New Jersey",179],["Texas",170],["Colorado",144],["Louisiana",115],["New York",99],["Oregon",71],["California",68],["Idaho",54],["New Mexico",51],["Washington",47],["Rhode Island",43],["Montana",37],["Utah",30],["Arizona",16]]},"kind":"categorical","n":3235,"n_null":0,"n_unique":25,"null_rate":0.0,"stats":{"cardinality":25,"entropy":3.8499134239209387,"entropy_ratio":0.8290337311474109,"top_rate":0.14775888717156105,"top_value":"Missouri"}}],"insights":{"errors":[],"insights":[{"confidence":"high","critiques":[],"evidence_keys":["row_count","column_count","deposit_type.top_values","deposit_type.top_rate","distance_to_deposit.skew","distance_to_deposit.median","distance_to_deposit.max","distance_to_deposit.mean","deposit_era.top_values","deposit_era.top_rate","deposit_state.top_values","state_name.top_values","state_name.cardinality"],"featured_charts":[{"caption":"Shows how heavily Coal dominates the deposit mix relative to metals and hydrocarbons.","column":"deposit_type","kind":"bar"},{"caption":"Highlights the strong right skew and the long tail of counties far from any deposit.","column":"distance_to_deposit","kind":"histogram"},{"caption":"Compares the nine geological eras, with Pennsylvanian leading and Permian trailing.","column":"deposit_era","kind":"donut"},{"caption":"Reveals which states host the most deposits feeding nearby counties, led by Missouri and Ohio.","column":"deposit_state","kind":"bar"},{"caption":"Confirms broad geographic coverage across states, with Texas and Georgia contributing the most county rows.","column":"state_name","kind":"bar"}],"model":"anthropic:claude-opus-4-7","narrative":"This dataset links 3,235 U.S. counties (by FIPS code) to their nearest geological mineral or fuel deposit, including the deposit's type, era, state, and distance. Coal dominates deposit_type at roughly 42% of rows, with Copper, Iron, and Oil rounding out the major categories \u2014 worth checking whether this reflects true geological prevalence or sampling bias. The distance_to_deposit column is heavily right-skewed (skew ~7.5, max 5652 vs. median 152), so a small number of remote counties pull the mean far above typical values and deserve a closer look. Deposit eras span nine geological periods led by Pennsylvanian (~23%), and deposit_state concentrates in Missouri, Ohio, and Alabama even though counties themselves are spread across all 56 state codes.","scope":"dataset","target":"__global__"},{"confidence":"high","critiques":[],"evidence_keys":["n","n_unique","null_rate","stats.min","stats.max","stats.iqr","stats.skew"],"model":"anthropic:claude-opus-4-7","narrative":"This is the FIPS code identifying U.S. counties (or equivalent geographies), with all 3235 values unique and no nulls. Values span 1001 to 78030, consistent with state-prefixed county codes, and the distribution is broad (IQR 27090) rather than meaningfully skewed (skew 0.17). Treat the numeric stats as incidental \u2014 magnitude has no quantitative meaning here.","role":"identifier","scope":"column","target":"fips","treatment":"Cast to string and use as a join key to county-level reference data; do not model as numeric."},{"confidence":"high","critiques":[],"evidence_keys":["n","n_unique","null_rate","stats.duplicate_rate","stats.n_duplicates","stats.len_mean","stats.word_mean","top_values","top_words"],"model":"anthropic:claude-opus-4-7","narrative":"This column holds US county-level place names, with 1,973 unique values across 3,235 rows and almost every entry containing the word 'county' (2,999 occurrences) alongside Louisiana 'parish' (64) and Puerto Rico 'municipio' (78) variants. Names repeat heavily \u2014 duplicate rate is 39% with classics like 'Washington County' (30), 'Jefferson County' (25), and 'Franklin County' (24) topping the list, which is expected since the same county name recurs across states. Entries are short (mean 14.2 chars, ~2 words) and there are no nulls or empties.","role":"metadata","scope":"column","target":"county_name","treatment":"Pair with a state column to form a unique geographic key before joining or aggregating."},{"confidence":"high","critiques":[],"evidence_keys":["n","n_unique","null_rate","stats.cardinality","stats.entropy_ratio","stats.top_value","stats.top_rate","top_values"],"model":"anthropic:claude-opus-4-7","narrative":"This is a US state code column with 56 unique values \u2014 more than the 50 states, suggesting territories or codes like DC, PR, or military designations are included. The distribution is fairly even (entropy ratio 0.92), with TX leading at 7.9% (254 of 3235 rows) followed by GA, VA, KY, and MO, consistent with a county- or jurisdiction-level dataset where larger states contribute more rows. No nulls.","role":"feature","scope":"column","target":"state","treatment":"One-hot or target-encode for modelling; verify the 6 extra codes beyond 50 states."},{"confidence":"high","critiques":[],"evidence_keys":["n","n_unique","null_rate","stats.cardinality","stats.entropy_ratio","stats.top_rate","stats.top_value","top_values"],"model":"anthropic:claude-opus-4-7","narrative":"This column holds U.S. state names, almost certainly one row per county or county-equivalent given the 3,235 total rows and 56 distinct values (the 50 states plus territories/DC). Texas dominates at 254 rows (7.85%), followed by Georgia (159) and Virginia (133), which matches the known county-count ranking. Distribution is highly even across categories (entropy ratio 0.92) with no nulls.","role":"feature","scope":"column","target":"state_name","treatment":"Use as a categorical grouping key; one-hot or target-encode for modelling."},{"confidence":"high","critiques":[],"evidence_keys":["n","n_unique","null_rate","stats.mean","stats.median","stats.min","stats.max","stats.q1","stats.q3","stats.std","stats.skew","stats.kurtosis","stats.n_outliers","stats.outlier_rate","stats.zero_rate"],"model":"anthropic:claude-opus-4-7","narrative":"Numeric feature measuring distance to a deposit, likely in metres, with all 3235 rows populated and 2202 distinct values. The distribution is severely right-skewed (skew 7.51, kurtosis 77.6): the median is 152.0 while the mean is 230.12 and the max stretches to 5652.4, more than 14x the Q3 of 235.75. About 4.9% of rows (159) flag as outliers, and there are no zeros or nulls.","role":"feature","scope":"column","target":"distance_to_deposit","treatment":"log-transform before modelling to tame the heavy right tail."},{"confidence":"high","critiques":[],"evidence_keys":["n","n_unique","null_rate","stats.cardinality","stats.entropy_ratio","stats.top_rate","stats.top_value","top_values"],"model":"anthropic:claude-opus-4-7","narrative":"This column names the nearest mineral deposit for each record, with 97 distinct sites across 3,235 rows and no nulls. Distribution is moderately concentrated: \"Hatchet Creek Copper\" alone accounts for 13.4% (434 rows), and the top three deposits cover roughly 30% of the data, yet entropy ratio of 0.76 indicates the long tail still carries meaningful spread. Names mix mine types (copper, clay, sulfur), pits, banks, quads, and districts, suggesting heterogeneous source nomenclature rather than a clean controlled vocabulary.","role":"feature","scope":"column","target":"nearest_deposit","treatment":"Treat as a high-cardinality categorical: target- or frequency-encode, and consider grouping rare deposits into an 'other' bucket."},{"confidence":"high","critiques":[],"evidence_keys":["n","n_unique","null_rate","stats.top_value","stats.top_rate","stats.entropy_ratio","top_values"],"model":"anthropic:claude-opus-4-7","narrative":"Categorical label identifying the type of mineral or fuel deposit, with 10 distinct values across 3235 rows and no nulls. Coal dominates at 41.6% (1345 rows), followed by Copper, Iron, and Oil, while Zinc (23) and Silver (21) are rare. Entropy ratio of 0.76 indicates a moderately concentrated distribution skewed toward fossil/base resources rather than precious metals.","role":"label","scope":"column","target":"deposit_type","treatment":"One-hot encode; consider grouping rare classes (Zinc, Silver) if used as a target."},{"confidence":"high","critiques":[],"evidence_keys":["n","n_unique","null_rate","stats.entropy_ratio","stats.top_rate","stats.top_value","top_values"],"model":"anthropic:claude-opus-4-7","narrative":"Categorical geological era/period label for deposits, spanning 9 distinct values across 3235 complete rows. Distribution is unusually flat for a categorical (entropy_ratio 0.945) \u2014 Pennsylvanian leads at only 22.6% (732 rows) and even the smallest, Permian, holds 95 rows. Note the mixed granularity: broad eras (Paleozoic, Precambrian) sit alongside specific periods (Devonian, Miocene), so categories are not mutually exclusive in geological time.","role":"feature","scope":"column","target":"deposit_era","treatment":"One-hot encode, but consider reconciling overlapping era/period granularity before modelling."},{"confidence":"high","critiques":[],"evidence_keys":["n","n_unique","null_rate","stats.entropy_ratio","stats.top_rate","stats.top_value","top_values"],"model":"anthropic:claude-opus-4-7","narrative":"`deposit_state` is a categorical US-state field with 25 distinct values across 3,235 rows and no nulls. Distribution is fairly even (entropy ratio 0.83); the top state Missouri accounts for only 14.8%, followed closely by Ohio (448) and Alabama (434). Coverage is partial \u2014 only half the US states appear \u2014 so this is not a nationwide sample.","role":"feature","scope":"column","target":"deposit_state","treatment":"One-hot or target-encode for modelling; verify whether the 25-state coverage is intentional."}],"providers":["anthropic:claude-opus-4-7"],"total_usage":{"completion_tokens":3391,"prompt_tokens":11250,"total_tokens":14641}},"language_counts":{},"meta":{"generated_at":"2026-05-01T17:27:52+00:00","mode":"full","row_count":3235,"sampled_rows":3235,"seed":42,"source":"/home/coolhand/html/datavis/data_trove/geographic/fips_county/geology_counties.csv"},"notes":[],"saturn_version":"0.2.0","schema":{"county_name":"text","deposit_era":"categorical","deposit_state":"categorical","deposit_type":"categorical","distance_to_deposit":"numeric","fips":"numeric","nearest_deposit":"categorical","state":"categorical","state_name":"categorical"}}