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| import math | |
| from sympy import divisor_sigma, isprime | |
| import time | |
| t1 = time.time() | |
| results = [] | |
| n = 1 | |
| while len(results) < 50: | |
| if n > 2 and isprime(n): | |
| n += 1 |
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| CHECKRANGE = LAMBDA(checkfn, | |
| LAMBDA(directionfn, | |
| LAMBDA(v, | |
| directionfn(v,LAMBDA(x,AND(checkfn(x)))) | |
| ))); | |
| CHECKISBLANK = CHECKRANGE(ISBLANK); | |
| CHECKBLANKROWS = CHECKISBLANK(BYROW); | |
| CHECKBLANKCOLS = CHECKISBLANK(BYCOL); | |
| TRIMRANGE2 =LAMBDA(sparseRange, [compressOrRemove], |
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| # Create a KPI card | |
| card = KPICard(figsize=(4, 3)) | |
| # Add elements to the card | |
| card.add_title("Revenue") | |
| card.add_value(1234567, prefix="$", suffix="") | |
| card.add_change(12.5) # Will show with arrow | |
| card.add_subtitle("vs. Previous Month") | |
| card.add_border() |
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| function main( | |
| workbook: ExcelScript.Workbook, | |
| outputRange: string = "A1", | |
| newSheetName: string = "Sheet Report" | |
| ) { | |
| const sheets = workbook.getWorksheets(); | |
| // Create or clear the report sheet | |
| let thisSheet = workbook.getWorksheet(newSheetName); | |
| if (thisSheet) { |
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| {"OrderDate","Category","SubCategory","Product","SalesAmount","OrderQuantity";40541,"Bikes","Road Bikes","Road-150 Red, 62",3578.27,1;40541,"Bikes","Mountain Bikes","Mountain-100 Silver, 44",3399.99,1;40541,"Bikes","Mountain Bikes","Mountain-100 Silver, 44",3399.99,1;40541,"Bikes","Road Bikes","Road-650 Black, 62",699.0982,1;40541,"Bikes","Mountain Bikes","Mountain-100 Silver, 44",3399.99,1;40542,"Bikes","Road Bikes","Road-150 Red, 44",3578.27,1;40542,"Bikes","Road Bikes","Road-150 Red, 62",3578.27,1;40542,"Bikes","Mountain Bikes","Mountain-100 Black, 48",3374.99,1;40542,"Bikes","Mountain Bikes","Mountain-100 Silver, 38",3399.99,1;40543,"Bikes","Road Bikes","Road-150 Red, 48",3578.27,1;40543,"Bikes","Road Bikes","Road-150 Red, 48",3578.27,1;40543,"Bikes","Road Bikes","Road-650 Red, 52",699.0982,1;40543,"Bikes","Road Bikes","Road-150 Red, 52",3578.27,1;40543,"Bikes","Road Bikes","Road-150 Red, 56",3578.27,1;40544,"Bikes","Road Bikes","Road-150 Red, 56",3578.27,1;40544,"Bikes","Road Bikes","Road-150 Red, 44",35 |
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| /* | |
| FINITE_DIFF function | |
| array is a vector (one column or one row) | |
| 1) Check if array is a vector. If not, return #VALUE! | |
| 2) Multiply array by similarly sized array of {1, -1, ..., -1}. | |
| 3) REDUCE SUM over (2) |
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| FIRST = LAMBDA(arr, INDEX(arr, 1, 1)); | |
| LAST = LAMBDA(arr, INDEX(arr, 1, 1)); | |
| RESAMPLE = LAMBDA(rule, | |
| LAMBDA(datetime_index, values, functions, | |
| LET( | |
| week_day, WEEKDAY(datetime_index, 2), | |
| date_year, YEAR(datetime_index), | |
| group_function, SWITCH( | |
| LOWER(rule), |
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| import subprocess | |
| result = subprocess.run(['pip', 'list'], capture_output=True, text=True) | |
| lines = result.stdout.splitlines()[2:] | |
| [tuple(line.split()[:2]) for line in lines] |
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| /* | |
| For a single data with sets of 'every' columns with differing counts of rows, | |
| trim each set and stack them on top of each other | |
| Dependencies: | |
| STACKER: | |
| https://gist.github.com/ncalm/ef7ed953571eec1475c291948aa2dbc3 | |
| EveryXtoN: | |
| https://gist.github.com/ncalm/48b96ac45685a7897fdf0a7336b2e96b |
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| /* | |
| Return every 'x' integers no larger than n, optionally skipping the first 'skip' | |
| integers in such a sequence | |
| e.g. | |
| EveryXtoN(10, 2) = {1; 3; 5; 7; 9} | |
| EveryXtoN(10, 2, 1) = {3; 5; 7; 9} | |
| EveryXtoN(10, 2, 2) = {5; 7; 9} | |
| EveryXtoN(10, 3) = {1; 4; 7; 10} |