How to sum a specific number of rows within a column?

Question

So I am working with a CSV file in RStudio. I am trying to find out in which row does the sum of the numbers in a specific column add up to cumulative number 0.8 (80%) (or a close value).

This is what the column looks like when I extract it

 [1] 0.165705620 0.087013121 0.066435240 0.058204088 0.046089979 0.044273757 0.038910088 0.038449322 0.027019652 0.026174169
 [11] 0.021463624 0.021065487 0.016690451 0.014252419 0.010874963 0.009340568 0.009192944 0.007493033 0.007475139 0.007403564
 [21] 0.007340935 0.006933851 0.006446245 0.006423877 0.006312041 0.006294147 0.006231519 0.006074948 0.005641023 0.005596289
 [31] 0.005046054 0.004992373 0.004285567 0.004088735 0.004079788 0.004075315 0.003838222 0.003762173 0.003574288 0.003493766
 [41] 0.003457979 0.003431138 0.003422191 0.003220886 0.003149310 0.003131417 0.003059841 0.002970372 0.002943532 0.002934585
 [51] 0.002916691 0.002863009 0.002809328 0.002733279 0.002424611 0.002415664 0.002402244 0.002361983 0.002187518 0.002174098
 [61] 0.002169624 0.002102523 0.002093576 0.002008580 0.001977266 0.001968319 0.001865430 0.001802801 0.001767014 0.001695438
 [71] 0.001690965 0.001588076 0.001588076 0.001538868 0.001529921 0.001516500 0.001449399 0.001418084 0.001382297 0.001324142
 [81] 0.001292828 0.001270460 0.001261514 0.001163098 0.001131783 0.001095996 0.001073629 0.001060208 0.001042314 0.001024421
 [91] 0.001006527 0.000979686 0.000979686 0.000975213 0.000966266 0.000926005 0.000908111 0.000908111 0.000881270 0.000876797
[101] 0.000854429 0.000845482 0.000832062 0.000787328 0.000787328 0.000782854 0.000769434 0.000733646 0.000724699 0.000697859
[111] 0.000693385 0.000693385 0.000671018 0.000671018 0.000657597 0.000644177 0.000639704 0.000621810 0.000612863 0.000581549
[121] 0.000572602 0.000572602 0.000572602 0.000550235 0.000536814 0.000536814 0.000532341 0.000523394 0.000514447 0.000509974
[131] 0.000505500 0.000505500 0.000501027 0.000496553 0.000492080 0.000469712 0.000469712 0.000465239 0.000451819 0.000442872
[141] 0.000438398 0.000429451 0.000429451 0.000424978 0.000416031 0.000416031 0.000411558 0.000407084 0.000407084 0.000389190
[151] 0.000389190 0.000384717 0.000380243 0.000380243 0.000375770 0.000366823 0.000348929 0.000339982 0.000339982 0.000339982
[161] 0.000335509 0.000335509 0.000331035 0.000317615 0.000317615 0.000313142 0.000313142 0.000304195 0.000299721 0.000299721
[171] 0.000295248 0.000286301 0.000281827 0.000281827 0.000277354 0.000272881 0.000272881 0.000268407 0.000263934 0.000259460
[181] 0.000259460 0.000259460 0.000254987 0.000250513 0.000237093 0.000232620 0.000228146 0.000228146 0.000228146 0.000223673
[191] 0.000223673 0.000223673 0.000210252 0.000205779 0.000201305 0.000201305 0.000201305 0.000201305 0.000196832 0.000196832
[201] 0.000196832 0.000192358 0.000187885 0.000187885 0.000183412 0.000183412 0.000178938 0.000174465 0.000174465 0.000169991
[211] 0.000169991 0.000169991 0.000169991 0.000165518 0.000165518 0.000161044 0.000161044 0.000156571 0.000156571 0.000156571
[221] 0.000152097 0.000152097 0.000152097 0.000152097 0.000152097 0.000152097 0.000152097 0.000147624 0.000147624 0.000147624
[231] 0.000143150 0.000138677 0.000138677 0.000138677 0.000138677 0.000134204 0.000129730 0.000120783 0.000120783 0.000116310
[241] 0.000116310 0.000116310 0.000116310 0.000111836 0.000111836 0.000111836 0.000111836 0.000107363 0.000107363 0.000107363
[251] 0.000107363 0.000102889 0.000102889 0.000102889 0.000098400 0.000098400 0.000093900 0.000093900 0.000093900 0.000093900
[261] 0.000093900 0.000093900 0.000089500 0.000089500 0.000089500 0.000089500 0.000089500 0.000089500 0.000085000 0.000085000
[271] 0.000085000 0.000080500 0.000080500 0.000080500 0.000076000 0.000076000 0.000076000 0.000071600 0.000071600 0.000071600
[281] 0.000071600 0.000067100 0.000067100 0.000067100 0.000067100 0.000067100 0.000067100 0.000062600 0.000062600 0.000062600
[291] 0.000062600 0.000058200 0.000058200 0.000058200 0.000058200 0.000058200 0.000058200 0.000058200 0.000058200 0.000053700
[301] 0.000053700 0.000053700 0.000053700 0.000053700 0.000053700 0.000053700 0.000053700 0.000049200 0.000049200 0.000049200
[311] 0.000049200 0.000049200 0.000049200 0.000049200 0.000049200 0.000044700 0.000044700 0.000044700 0.000044700 0.000044700
[321] 0.000044700 0.000044700 0.000044700 0.000044700 0.000044700 0.000044700 0.000044700 0.000044700 0.000044700 0.000044700
[331] 0.000044700 0.000040300 0.000040300 0.000040300 0.000040300 0.000040300 0.000040300 0.000040300 0.000040300 0.000040300
[341] 0.000040300 0.000035800 0.000035800 0.000035800 0.000035800 0.000035800 0.000035800 0.000035800 0.000035800 0.000035800
[351] 0.000035800 0.000035800 0.000035800 0.000035800 0.000035800 0.000031300 0.000031300 0.000031300 0.000031300 0.000031300
[361] 0.000031300 0.000031300 0.000031300 0.000031300 0.000031300 0.000031300 0.000026800 0.000026800 0.000026800 0.000026800
[371] 0.000026800 0.000026800 0.000026800 0.000026800 0.000026800 0.000026800 0.000026800 0.000026800 0.000026800 0.000026800
[381] 0.000026800 0.000026800 0.000022400 0.000022400 0.000022400 0.000022400 0.000022400 0.000022400 0.000022400 0.000022400
[391] 0.000022400 0.000022400 0.000022400 0.000022400 0.000022400 0.000022400 0.000022400 0.000022400 0.000022400 0.000022400
[401] 0.000022400 0.000022400 0.000022400 0.000017900 0.000017900 0.000017900 0.000017900 0.000017900 0.000017900 0.000017900
[411] 0.000017900 0.000017900 0.000017900 0.000017900 0.000017900 0.000017900 0.000017900 0.000017900 0.000017900 0.000017900
[421] 0.000017900 0.000017900 0.000017900 0.000017900 0.000017900 0.000017900 0.000017900 0.000017900 0.000017900 0.000017900
[431] 0.000017900 0.000017900 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400
[441] 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400
[451] 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400
[461] 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400 0.000013400 0.000008950 0.000008950 0.000008950 0.000008950
[471] 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950
[481] 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950
[491] 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950
[501] 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950
[511] 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950 0.000008950
[521] 0.000008950 0.000008950 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470
[531] 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470
[541] 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470
[551] 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470
[561] 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470
[571] 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470
[581] 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470
[591] 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470
[601] 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470
[611] 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470
[621] 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470 0.000004470
[631] 0.000004470

I tried using the sum function but couldn't figure out a way to sum a specific amount of rows so the function ends up summing the entire row.

library(ggplot2)

#Step 1

SumWeldInfo <- read.csv(file="C:\\Users\\ahmed\\Documents\\Assignment 4\\sum_weld_info.csv", header=TRUE, sep=",")
sum(SumWeldInfo$work.proportion)

I have also tried messing around with ggplots to see if there's a way to graph it out and figure out the number but no luck graphing the cumalative percentage. I could only graph the individual percentages.

So basically I need a function that lets me sum up a specific amount of rows in this column within a csv file OR a function that lets the sum of a specific amount of rows equal to 0.8 and outputs how many rows it took to reach that number

Answer 1

You can use which.max to select the first TRUE value from the logcial vector created by checking the cumsum agaisnt your cutoff threshold (in this case, 0.8), and it will give you the first time the cumsum of your column is greater than or equal to 0.8:

which.max(cumsum(your_col) >= .8)
[1] 33

In the future, please include a dput() of your output, or some way for users to create a reproducible example of your question.

Data:

your_col <- c(0.165705620, 0.087013121, 0.066435240, 0.058204088, 0.046089979, 0.044273757, 0.038910088, 0.038449322, 0.027019652, 0.026174169, 
0.021463624, 0.021065487, 0.016690451, 0.014252419, 0.010874963, 0.009340568, 0.009192944, 0.007493033, 0.007475139, 0.007403564, 
0.007340935, 0.006933851, 0.006446245, 0.006423877, 0.006312041, 0.006294147, 0.006231519, 0.006074948, 0.005641023, 0.005596289, 
0.005046054, 0.004992373, 0.004285567, 0.004088735, 0.004079788, 0.004075315, 0.003838222, 0.003762173, 0.003574288, 0.003493766, 
0.003457979, 0.003431138, 0.003422191, 0.003220886, 0.003149310, 0.003131417, 0.003059841, 0.002970372, 0.002943532, 0.002934585, 
0.002916691, 0.002863009, 0.002809328, 0.002733279, 0.002424611, 0.002415664, 0.002402244, 0.002361983, 0.002187518, 0.002174098, 
0.002169624, 0.002102523, 0.002093576, 0.002008580, 0.001977266, 0.001968319, 0.001865430, 0.001802801, 0.001767014, 0.001695438, 
0.001690965, 0.001588076, 0.001588076, 0.001538868, 0.001529921, 0.001516500, 0.001449399, 0.001418084, 0.001382297, 0.001324142, 
0.001292828, 0.001270460, 0.001261514, 0.001163098, 0.001131783, 0.001095996, 0.001073629, 0.001060208, 0.001042314, 0.001024421,
0.001006527, 0.000979686, 0.000979686, 0.000975213, 0.000966266, 0.000926005, 0.000908111, 0.000908111, 0.000881270, 0.000876797, 
0.000854429, 0.000845482, 0.000832062, 0.000787328, 0.000787328, 0.000782854, 0.000769434, 0.000733646, 0.000724699, 0.000697859, 
0.000693385, 0.000693385, 0.000671018, 0.000671018, 0.000657597, 0.000644177, 0.000639704, 0.000621810, 0.000612863, 0.000581549, 
0.000572602, 0.000572602, 0.000572602, 0.000550235, 0.000536814, 0.000536814, 0.000532341, 0.000523394, 0.000514447, 0.000509974,
0.000505500, 0.000505500, 0.000501027, 0.000496553, 0.000492080, 0.000469712, 0.000469712, 0.000465239, 0.000451819, 0.000442872, 
0.000438398, 0.000429451, 0.000429451, 0.000424978, 0.000416031, 0.000416031, 0.000411558, 0.000407084, 0.000407084, 0.000389190, 
0.000389190, 0.000384717, 0.000380243, 0.000380243, 0.000375770, 0.000366823, 0.000348929, 0.000339982, 0.000339982, 0.000339982, 
0.000335509, 0.000335509, 0.000331035, 0.000317615, 0.000317615, 0.000313142, 0.000313142, 0.000304195, 0.000299721, 0.000299721,
0.000295248, 0.000286301, 0.000281827, 0.000281827, 0.000277354, 0.000272881, 0.000272881, 0.000268407, 0.000263934, 0.000259460, 
0.000259460, 0.000259460, 0.000254987, 0.000250513, 0.000237093, 0.000232620, 0.000228146, 0.000228146, 0.000228146, 0.000223673,
0.000223673, 0.000223673, 0.000210252, 0.000205779, 0.000201305, 0.000201305, 0.000201305, 0.000201305, 0.000196832, 0.000196832, 
0.000196832, 0.000192358, 0.000187885, 0.000187885, 0.000183412, 0.000183412, 0.000178938, 0.000174465, 0.000174465, 0.000169991, 
0.000169991, 0.000169991, 0.000169991, 0.000165518, 0.000165518, 0.000161044, 0.000161044, 0.000156571, 0.000156571, 0.000156571,
0.000152097, 0.000152097, 0.000152097, 0.000152097, 0.000152097, 0.000152097, 0.000152097, 0.000147624, 0.000147624, 0.000147624, 
0.000143150, 0.000138677, 0.000138677, 0.000138677, 0.000138677, 0.000134204, 0.000129730, 0.000120783, 0.000120783, 0.000116310, 
0.000116310, 0.000116310, 0.000116310, 0.000111836, 0.000111836, 0.000111836, 0.000111836, 0.000107363, 0.000107363, 0.000107363,
0.000107363, 0.000102889, 0.000102889, 0.000102889, 0.000098400, 0.000098400, 0.000093900, 0.000093900, 0.000093900, 0.000093900, 
0.000093900, 0.000093900, 0.000089500, 0.000089500, 0.000089500, 0.000089500, 0.000089500, 0.000089500, 0.000085000, 0.000085000, 
0.000085000, 0.000080500, 0.000080500, 0.000080500, 0.000076000, 0.000076000, 0.000076000, 0.000071600, 0.000071600, 0.000071600, 
0.000071600, 0.000067100, 0.000067100, 0.000067100, 0.000067100, 0.000067100, 0.000067100, 0.000062600, 0.000062600, 0.000062600,
0.000062600, 0.000058200, 0.000058200, 0.000058200, 0.000058200, 0.000058200, 0.000058200, 0.000058200, 0.000058200, 0.000053700, 
0.000053700, 0.000053700, 0.000053700, 0.000053700, 0.000053700, 0.000053700, 0.000053700, 0.000049200, 0.000049200, 0.000049200,
0.000049200, 0.000049200, 0.000049200, 0.000049200, 0.000049200, 0.000044700, 0.000044700, 0.000044700, 0.000044700, 0.000044700, 
0.000044700, 0.000044700, 0.000044700, 0.000044700, 0.000044700, 0.000044700, 0.000044700, 0.000044700, 0.000044700, 0.000044700, 
0.000044700, 0.000040300, 0.000040300, 0.000040300, 0.000040300, 0.000040300, 0.000040300, 0.000040300, 0.000040300, 0.000040300,
0.000040300, 0.000035800, 0.000035800, 0.000035800, 0.000035800, 0.000035800, 0.000035800, 0.000035800, 0.000035800, 0.000035800, 
0.000035800, 0.000035800, 0.000035800, 0.000035800, 0.000035800, 0.000031300, 0.000031300, 0.000031300, 0.000031300, 0.000031300, 
0.000031300, 0.000031300, 0.000031300, 0.000031300, 0.000031300, 0.000031300, 0.000026800, 0.000026800, 0.000026800, 0.000026800, 
0.000026800, 0.000026800, 0.000026800, 0.000026800, 0.000026800, 0.000026800, 0.000026800, 0.000026800, 0.000026800, 0.000026800, 
0.000026800, 0.000026800, 0.000022400, 0.000022400, 0.000022400, 0.000022400, 0.000022400, 0.000022400, 0.000022400, 0.000022400, 
0.000022400, 0.000022400, 0.000022400, 0.000022400, 0.000022400, 0.000022400, 0.000022400, 0.000022400, 0.000022400, 0.000022400, 
0.000022400, 0.000022400, 0.000022400, 0.000017900, 0.000017900, 0.000017900, 0.000017900, 0.000017900, 0.000017900, 0.000017900,
0.000017900, 0.000017900, 0.000017900, 0.000017900, 0.000017900, 0.000017900, 0.000017900, 0.000017900, 0.000017900, 0.000017900, 
0.000017900, 0.000017900, 0.000017900, 0.000017900, 0.000017900, 0.000017900, 0.000017900, 0.000017900, 0.000017900, 0.000017900, 
0.000017900, 0.000017900, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 
0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 
0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400,
0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000013400, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 
0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 
0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 
0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950,
0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 
0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 0.000008950, 
0.000008950, 0.000008950, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 
0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 
0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 
0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 
0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 
0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 
0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 
0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 
0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 
0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470,
0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470, 0.000004470)

Answer 2

As you have specified that you want to know how many rows should it take to sum upto 0.8, I guess you require random rows from your list of rows that sum upto 0.8. So what you can do is that start with 1 row and start increasing the number of rows till you get the sum =0.8.

If you can give me your data as a reproducible example, I will suggest you how to do it. Please give me your above data in a format so that it can be loaded into R.