29 lines
1.4 KiB
R
Executable File
29 lines
1.4 KiB
R
Executable File
##Final R assignment in Intro to Statistics course, fall semster.
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#+Written by Matan Horovitz (207130253) and Guy Amzaleg ()
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#+We have chosen a dataset of CPU and GPU performance trends since 2000 - as published on Kaggle:
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#+https://www.kaggle.com/datasets/michaelbryantds/cpu-and-gpu-product-data
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raw_perf_data <- read.csv("/home/shmick/Downloads/chip_dataset.csv")
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##BONUS: convert from EPOCH: as.Date(as.POSIXct(1100171890,origin = "1970-01-01"))
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View(raw_perf_data)
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##For question 1, we have chosen to examine which type of chip has examined the greater improvement over the years - GPU chips or CPU chips.
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#+As chip perfomance is most directly correlated with the number of transistors, we have measured the pace of development based on pace of
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#+increasing transistor count.
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CPU <- chip[chip$Type == 'CPU',]
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GPU <- chip[chip$Type == 'GPU',]
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CPU_Transistor_Count <- order(CPU$Transistors..million.)
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GPU_Transistor_Count <- order(GPU$Transistors..million.)
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##Iterate over date entries
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for (i in 1:length(CPU$Release.Date)){print(i)}
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##Get date
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for (i in 1:length(CPU$Release.Date)){print(CPU$Release.Date[i])}
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##QUESTION 2: measure number of columns in our dataset and calculate a permutation and combination of
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#+that number, minus two, and 3.
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#Calculate total number of columns in our dataset
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n <- ncol(kernel_commits)
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View(n)
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##QUESTION 3: pick two categorial variables - month (?), is documentation |