updating with new descriptive stats for the methods section following data cleaning
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@ -4,12 +4,11 @@ main_df <- read.csv(main_csv, header = TRUE)
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bz_summary <- main_df |>
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bz_summary <- main_df |>
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mutate(isBz = if_else(
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mutate(isBz = if_else(
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AuthorPHID == "PHID-USER-ynivjflmc2dcl6w5ut5v", TRUE, FALSE
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AuthorPHID == "PHID-USER-idceizaw6elwiwm5xshb", TRUE, FALSE
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)) |>
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)) |>
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group_by(source, comment_type)|>
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group_by(source, comment_type, isBz)|>
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summarise(count = n(), .groups = 'drop')
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summarise(count = n(), .groups = 'drop')
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needs_triage <- dsl_df |>
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needs_triage <- dsl_df |>
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filter(week_index >= -4) |>
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filter(week_index >= -4) |>
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@ -1,17 +0,0 @@
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1. SSH tunnel from your workstation using the following command:
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ssh -N -L 8787:n3441:34063 mjilg@klone.hyak.uw.edu
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and point your web browser to http://localhost:8787
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2. log in to RStudio Server using the following credentials:
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user: mjilg
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password: mGALb8Ae1rRJIi4jmNUf
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When done using RStudio Server, terminate the job by:
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1. Exit the RStudio Session ("power" button in the top right corner of the RStudio window)
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2. Issue the following command on the login node:
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scancel -f 31867859
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