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employees for each department in the past year? Include the department name, month, year, and hire count.": [-0.016680246219038963, 0.009431988932192326, 0.03938315436244011, 0.02310379222035408, -0.04720279574394226, -0.026873944327235222, -0.007197021972388029, 0.013776063919067383, -0.04307544603943825, 0.028657609596848488, 0.009309608489274979, 0.045727234333753586, -0.033632874488830566, 0.0342920646071434, -0.028301039710640907, -0.027149483561515808, -0.003884644713252783, 0.0399959497153759, -0.00814015232026577, -0.018800320103764534, 0.02093544788658619, -0.010358882136642933, 0.0006865969044156373, 0.013786680996418, 0.02153737097978592, -0.025179356336593628, -0.015990927815437317, 0.054145000874996185, 0.0033110473304986954, 0.015279671177268028, -0.0007008895627222955, 0.013883942738175392, 0.06498625129461288, 0.04638136178255081, 0.07300713658332825, 0.0005210701492615044, 0.0067970603704452515, -0.03453218191862106, 0.016553299501538277, 0.0048698242753744125, -0.045474398881196976, -0.04331868886947632, 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decreased. 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-0.024344582110643387], "Generate a hierarchical org chart showing each employee, their direct reports (up to 3 levels deep), and the total salary budget for each sub-tree. The result should display the employee name, their level in the hierarchy, the number of direct reports, and the total salary budget for their sub-tree. Sort the results to show the hierarchy clearly.": [-0.04633290320634842, 0.03910137340426445, 0.03634442761540413, 0.020340651273727417, 0.001618382055312395, -0.047891292721033096, 0.0017292924458160996, -0.008779414929449558, 0.011814619414508343, 0.018566103652119637, -0.03441964462399483, 0.03088962286710739, -0.03785080462694168, 0.02923961542546749, -0.0064492919482290745, -0.04626503959298134, 0.023578690364956856, -0.006526986137032509, -0.0036993566900491714, 0.0096886046230793, -0.028381548821926117, 0.02183546870946884, -0.01070249080657959, 0.025387585163116455, 0.04131465032696724, -0.048080138862133026, -0.015757346525788307, 0.044338423758745193, 0.02547363005578518, 0.006724068429321051, 0.0027433126233518124, -0.019108381122350693, 0.005994291976094246, 0.04853371903300285, 0.06409098207950592, 0.032409727573394775, 0.019926531240344048, -0.044177208095788956, 0.013709398917853832, 0.0035484638065099716, -0.030312035232782364, -0.019359612837433815, 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department. For each department, show: 1. The employee with the longest tenure. 2. The employee with the highest salary increase percentage in the last year. 3. The 'rising star' (employee with less than 2 years tenure but in the top 10% of salary increases). 4. The retention rate (percentage of employees who have been with the company for more than 2 years). 5. The performance index (average of salary increase percentages for employees with more than 2 years tenure). 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For each department, display the department name, total salary cost, number of employees, average salary, and a calculated efficiency score. The efficiency score is the ratio of the department's average salary to the company-wide average salary, multiplied by the number of employees. Rank the departments by their efficiency score in descending order.": [-0.03206729143857956, 0.024084653705358505, 0.022964423522353172, 0.030709195882081985, -0.02943451888859272, -0.04513271525502205, -0.004983835853636265, -0.004175922833383083, -0.012262978591024876, 0.041173163801431656, -0.05531426519155502, 0.03682367503643036, -0.03425178304314613, 0.016680633649230003, -0.0237746424973011, -0.038426563143730164, 0.025814158841967583, 0.008845490403473377, -0.01536552980542183, 0.011764592491090298, -0.0033984766341745853, 0.018753409385681152, -0.01520018745213747, 0.004599211271852255, 0.019968673586845398, -0.03863943740725517, -0.005979720503091812, 0.05118763446807861, 0.04738732427358627, 0.006300860084593296, -0.014751902781426907, -0.01015770249068737, 0.01636195182800293, 0.07553479820489883, 0.05120323970913887, 0.0427854061126709, 0.011458335444331169, -0.03619446977972984, 0.00023206956393551081, 0.03958014026284218, -0.0549190454185009, -0.03299684822559357, 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0.04682466760277748, 0.015828678384423256, 0.001024633995257318, -0.04184667021036148, -0.017543787136673927, 0.038941726088523865, 0.011889470741152763, -0.009404518641531467, -0.03775192052125931, -0.01379070058465004, 0.0750824362039566, 0.006158590782433748, -5.15222673129756e-05, -0.03266088292002678, -0.006560673471540213, -0.004863671027123928, -0.020990919321775436, -0.038707491010427475, 0.03019781783223152, -0.02585006318986416, 0.00428165914490819, 0.009446799755096436, -0.008811036124825478, 0.021009989082813263, 0.006978112272918224, -0.025969378650188446, -0.050966013222932816, 0.019004179164767265, -0.030603617429733276, 0.006923748645931482, -0.015631111338734627, 0.015039080753922462, 0.008691757917404175, 0.041808173060417175, 0.019008846953511238, -0.03177247196435928, 0.06888344883918762, 0.03663096949458122, 0.03757913038134575, -0.062025681138038635, -0.06888386607170105], "Perform a salary quartile analysis for each department. For each department, calculate the salary quartiles (Q1, Q2, Q3) and then categorize each employee into their respective quartile. The final report should show the department name, employee name, their salary, their quartile category (1, 2, 3, or 4), and the percentage of employees in each quartile for that department.": [-0.028540050610899925, -0.004691844340413809, 0.011286486871540546, 0.030701978132128716, -0.012638965621590614, -0.07679476588964462, 0.0022544555831700563, 0.007321307435631752, -0.01713072881102562, 0.018388601019978523, -0.0032487190328538418, 0.047597210854291916, -0.032380059361457825, 0.00297808856703341, -0.026817359030246735, -0.059788383543491364, 0.00737316720187664, 0.008975546807050705, -0.010373065248131752, 0.0031047388911247253, -0.0020726758521050215, 0.00027163256891071796, 0.022953258827328682, 0.01439812034368515, 0.019208315759897232, -0.004428652115166187, -0.031200913712382317, 0.025317447260022163, 0.04717901349067688, 0.012533122673630714, -0.02579953335225582, 0.0018847038736566901, 0.015296265482902527, 0.07952424138784409, 0.06898661702871323, 0.034154441207647324, 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0.03797085955739021, 0.04246694594621658, 0.04105619713664055, -0.07476676255464554, -0.03677423670887947], "Analyze employee tenure across departments. For each department, show the number of employees who have been with the company for less than 1 year, 1-3 years, 3-5 years, and more than 5 years. Also, calculate the average salary for each tenure group. Finally, identify the department with the highest retention rate (percentage of employees with more than 3 years of tenure).": [-0.03241045027971268, 0.04322545975446701, 0.01076881866902113, 0.049331001937389374, -0.03693730756640434, -0.042574454098939896, 0.0026598672848194838, -0.0013801680179312825, -0.021067112684249878, 0.021612469106912613, 0.014036501757800579, 0.04107201471924782, -0.059749964624643326, 0.02096756175160408, -0.018313290551304817, -0.039078280329704285, 0.016564613208174706, 0.03592384234070778, 0.002986356383189559, 0.0010881718480959535, 0.008372430689632893, 0.0005230230162851512, 0.001305165234953165, 0.013777569867670536, 0.015500230714678764, -0.03248147666454315, -0.018335042521357536, 0.06174122169613838, 0.019534297287464142, 0.006207185331732035, -0.01696167327463627, 0.015949014574289322, 0.047073520720005035, 0.06920745968818665, 0.051244135946035385, 0.005877455696463585, 0.025963712483644485, -0.04213756322860718, 0.020705362781882286, 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Then, identify any salary outliers, defined as salaries below Q1 - 1.5*IQR or above Q3 + 1.5*IQR. Report the department name, median salary, IQR, number of outliers, and the percentage of outliers in the department. 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tenure and promotions. For each department, show the average time to promotion (assume a promotion is a salary increase of more than 15% in a year), the employee with the fastest promotion, and the percentage of employees who have been promoted in the last 2 years. Only consider employees who have been with the company for at least 1 year.": [-0.023133007809519768, 0.0311458520591259, 0.026612868532538414, 0.021821940317749977, -0.021076027303934097, -0.03457168489694595, 0.021084889769554138, 0.00011032811016775668, -0.04076604172587395, 0.0024920383002609015, 0.013905429281294346, 0.04779694974422455, -0.04998049885034561, 0.006988987326622009, -0.030154941603541374, -0.043701764196157455, 0.027788355946540833, 0.01969258114695549, -0.02585509419441223, 0.03347881883382797, 0.014716283418238163, 0.0020367116667330265, 0.004761467222124338, 0.012314265593886375, -0.007791440933942795, -0.026333417743444443, -0.028727728873491287, 0.07411332428455353, 0.01886768452823162, -0.008624340407550335, -0.0257700365036726, 0.022824661806225777, 0.05040885508060455, 0.07240351289510727, 0.08346114307641983, 0.021974919363856316, 0.008538507856428623, -0.04901665076613426, 0.02162007987499237, 0.0054083713330328465, -0.06508422642946243, 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Calculate the percentage of total salary budget each department consumes. Then, for each department, show the top 3 highest-paid employees and what percentage of the department's budget their salaries represent. Finally, calculate a 'budget efficiency' score for each department, defined as the department's percentage of total employees divided by its percentage of total salary budget.": [-0.038250647485256195, 0.010370016098022461, -0.004324824083596468, 0.023022569715976715, -0.013854880817234516, -0.03702953830361366, -0.002697406802326441, -0.017187682911753654, -0.0255037322640419, 0.03438761457800865, -0.001957703847438097, 0.0432908795773983, -0.02868032082915306, 0.01930207386612892, -0.024616412818431854, -0.013633656315505505, 0.027812477201223373, 0.008433526381850243, 0.0004343128821346909, 0.014566605910658836, 0.016202665865421295, 0.01668396405875683, -0.0038721857126802206, 0.02676207758486271, 0.0357363224029541, -0.02170749381184578, -0.02008972316980362, 0.07670095562934875, 0.041103776544332504, 0.006102899555116892, -0.015496420674026012, -0.001657484332099557, 0.03556591272354126, 0.07950583845376968, 0.06957658380270004, 0.007776355836540461, 0.003122980473563075, 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-0.06383053958415985, -0.04941343888640404], "Analyze employee performance trends over the past 3 years. For each department, identify employees who have had consistent salary increases (any increase each year) and those who have had at least one year without an increase. Calculate the average percentage increase for each group. Then, for each department, show the percentage of employees in each category and whether the department is 'improving' (more consistent increases than not) or 'needs attention'.": [-0.02747439034283161, 0.021301016211509705, 0.005380896385759115, 0.03136161342263222, -0.027049187570810318, -0.04501057788729668, -0.034105103462934494, 0.003085346659645438, -0.019196152687072754, 0.008214113302528858, -0.0010250565828755498, 0.04243892803788185, -0.025441590696573257, -0.018799468874931335, -0.016333024948835373, -0.012583741918206215, 0.01548337284475565, 0.034035179764032364, -0.008163276128470898, 0.020991835743188858, 0.0013488566037267447, -0.01825021207332611, -0.001133970101363957, 0.02990676462650299, 0.005987886339426041, -0.0011056012008339167, -0.038655832409858704, 0.04766795411705971, 0.029519585892558098, -0.015193779952824116, -0.04485822841525078, 0.0019146202830597758, 0.03780479356646538, 0.0473746731877327, 0.07154694199562073, 0.024625638499855995, 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0.013837632723152637, -0.0894700288772583, -0.025983735918998718], "Analyze inter-department collaboration based on project assignments. Assuming there's a 'projects' table with columns (id, name, start_date, end_date) and a 'project_assignments' table with columns (project_id, employee_id, role), calculate the following: 1) For each department, the number of projects they're involved in, 2) The top 3 department pairs that collaborate most frequently, 3) For each department, the employee who has worked on the most inter-department projects, and 4) The 'collaboration score' for each department (defined as the ratio of inter-department projects to total projects).": [-0.004288488067686558, 0.05299779772758484, 0.02546711266040802, 0.014712121337652206, -0.027856705710291862, -0.027814382687211037, 0.006936448160558939, 0.0015091252280399203, 0.0019316131947562099, 0.03623047098517418, -0.012199227698147297, 0.027432307600975037, -0.02701275609433651, 0.008146251551806927, -0.017147041857242584, -0.015186984091997147, 0.013239597901701927, 0.022594541311264038, -0.008642665110528469, -0.017086317762732506, 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Weigh these factors equally on a scale of 0-100. Then, for each department, show the average churn risk score, the number of high-risk employees (score > 70), and suggest the top 3 employees who might need immediate attention.": [-0.014093195088207722, 0.0357186421751976, 0.03215518593788147, 0.01038049440830946, -0.025480611249804497, -0.022287752479314804, 0.01017217431217432, -0.028251387178897858, -0.02840305119752884, -0.0020387747790664434, 0.027122534811496735, 0.04002232477068901, -0.03716890141367912, 0.004569411277770996, -0.03063810244202614, -0.05214357748627663, 0.011742980219423771, 0.02977140247821808, -0.022236434742808342, -0.010415475815534592, -5.7992547226604074e-05, 0.011044898070394993, -0.002474710578098893, 0.03975062444806099, 0.012727185152471066, 0.0025841868482530117, -0.014950192533433437, 0.055261269211769104, 0.017460301518440247, 0.015371834859251976, -0.002676054835319519, 0.011135950684547424, 0.0479188971221447, 0.05994202569127083, 0.0998876541852951, 0.03960298001766205, 0.002186152618378401, 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-0.07310912013053894, -0.04581136256456375], "Analyze the company's hiring patterns over the years. For each department and each quarter, calculate the number of new hires. Then identify any seasonal patterns by comparing each quarter's hiring numbers to the yearly average. Finally, predict the number of hires expected in the next quarter for each department based on the average trend of the same quarter over the past 3 years.": [-0.019090237095952034, 0.017534848302602768, 0.002000312553718686, 0.03244771063327789, -0.017526622861623764, -0.014562271535396576, -0.0046554384753108025, -0.00873501691967249, -0.04652035981416702, 0.009380710311233997, 0.0019625015556812286, 0.01298237219452858, -0.0015574335120618343, 0.02795696258544922, -0.03996622562408447, -0.04324294254183769, -0.01250364352017641, 0.05547558143734932, -0.0183180533349514, -0.013947994448244572, 0.028929391875863075, 0.005061243195086718, 0.01585393026471138, 0.0070899007841944695, 0.028891442343592644, -0.028981100767850876, -0.012548169121146202, 0.03067571111023426, 0.0028557179030030966, 0.017047666013240814, -0.02638399414718151, 0.013811721466481686, 0.0417705699801445, 0.05403464660048485, 0.08249116688966751, 0.007475962862372398, 0.02604358270764351, -0.011946175247430801, 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For each current job title, identify the top 3 previous job titles that employees held, along with the average time spent in each previous role. Then, for each job title, predict the most likely next career move based on historical data, and calculate the average time it takes to reach this next position.": [0.006430452223867178, 0.02057083137333393, 0.018729647621512413, 0.04623516649007797, -0.021681014448404312, -0.008990217931568623, 0.008911601267755032, -0.009966949000954628, -0.0255238376557827, -0.011717915534973145, -0.002589988987892866, 0.027681412175297737, -0.02310325764119625, 0.006706953980028629, -0.03380263224244118, 0.0013401604956015944, -0.026628578081727028, 0.04270089790225029, -0.005870345048606396, -0.002556457184255123, 0.0005465808790177107, -0.03102029114961624, 0.0028064176440238953, 0.021250858902931213, 0.03872304409742355, -0.02123003639280796, 0.005860175006091595, 0.040813468396663666, 0.0178380087018013, 0.015816815197467804, -0.005397203844040632, 0.005725613329559565, 0.0660649910569191, 0.057574864476919174, 0.0684523731470108, 0.01444828137755394, 0.024326173588633537, -0.02206229232251644, 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profitability of projects. Assuming there's a 'projects' table with columns (id, name, start_date, end_date, budget, revenue) and a 'project_assignments' table with columns (project_id, employee_id, hours_worked), calculate the following for each project: 1) Total labor cost (based on employees' hourly rates), 2) Profit margin, 3) Revenue per hour worked. Then, for each department, show the average profit margin of their projects, their most profitable project, and suggest the top 3 employees who contributed to highly profitable projects (considering their hours worked and the project's profitability).": [0.005684516858309507, 0.033851899206638336, -0.0011161351576447487, 0.0391162745654583, -0.03494071215391159, -0.026220498606562614, -0.015227744355797768, -0.0047297291457653046, -0.005685850977897644, 0.019052937626838684, 7.538178761024028e-05, 0.02392107993364334, -0.02683563157916069, 0.0313442125916481, -0.024997102096676826, -0.03374125063419342, -0.017745506018400192, 0.005807585548609495, 0.010568017140030861, 0.034948162734508514, -0.0017429993022233248, 0.021953528746962547, -0.015021379105746746, 0.025090709328651428, 0.033562518656253815, -0.006704256869852543, -0.02269287407398224, 0.03971923515200615, -0.007494888734072447, 0.021262817084789276, -0.014022765681147575, 0.033118147403001785, 0.023341001942753792, 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Assuming there's a 'skills' table with columns (id, name, category), an 'employee_skills' table with columns (employee_id, skill_id, proficiency_level), and a 'job_required_skills' table with columns (job_title, skill_id, required_level), perform the following analysis: 1) For each employee, calculate their skill match percentage for their current job title, 2) Identify the top 3 skills each employee should develop to improve their job fit, 3) For each department, show the average skill match percentage and the skills that are most lacking. Finally, suggest potential internal candidates for open positions based on skill match, considering only employees with at least 80% skill match to the open position's requirements.": [-0.019706662744283676, 0.01939413882791996, 0.00784918200224638, 0.011856155470013618, -0.04467448592185974, -0.026855170726776123, -0.014491685666143894, 0.0070108999498188496, -0.01618364080786705, 0.014236070215702057, 0.007757931016385555, 0.024225862696766853, -0.02130040153861046, 0.0107857221737504, -0.05344434455037117, 0.0013149650767445564, 0.004723754711449146, 0.0559401661157608, 0.010964310728013515, 0.020485205575823784, 0.028825607150793076, -0.005428093019872904, -0.025884248316287994, 0.011420917697250843, 0.034560978412628174, 0.006239027250558138, -0.03747450187802315, 0.029607106000185013, 0.03436300531029701, 0.025539692491292953, -0.03976743668317795, -0.0042512137442827225, 0.01931954175233841, 0.05243207886815071, 0.0631767138838768, 0.03075726330280304, 0.013800416141748428, 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skills/text_to_sql/data/vector_db.pkl (139 lines of code) (raw):