Finished bar plots. Merged bar and line plots into a single plot script.
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@ -1,6 +1,7 @@
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#!/usr/bin/env Rscript
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# Libraries:
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library(reshape2)
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library(tidyverse)
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# Parsing command line arguments:
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@ -8,19 +9,8 @@ options = commandArgs(trailingOnly = TRUE)
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filename = options[1]
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table_header = options[-1]
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# Loading files:
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table = read.csv(filename, col_names = table_header, row.names = length(table_header)) # The last column of the table gives the timestamp, thus the row names
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# Setting up the table so it can be plotted:
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# Transposing for bar plotting:
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table = t(as.matrix(table))
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# Plotting:
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barplot(table)
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# legend("topright", legend = c("Level 1", "Level 2"), fill = c("red", "darkblue"))
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# read.csv(filename, col_names = table_header, row.names = length(table_header) + 1) %>% # The last column of the table gives the timestamp, thus the row names
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# mutate(timestamp = as_date(as_datetime(timestamp))) %>% # Formatting the date
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# as.matrix() %>% # Converting to matrix to transpose
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# t() %>% # Transposing for bar plotting
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# barplot()
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read_csv(filename, col_names = table_header) %>%
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mutate(timestamp = as_date(as_datetime(timestamp))) %>% # Formatting the date
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melt(id.vars = "timestamp", variable.name = "category", value.name = "amount") %>% # Formatting the table to plot each category
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ggplot(aes(x = timestamp, y = amount, fill = category)) +
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geom_bar(stat = "identity")
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@ -9,7 +9,7 @@ options = commandArgs(trailingOnly = TRUE)
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filename = options[1]
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table_header = options[-1]
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read_csv(filename, col_names=table_header) %>%
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read_csv(filename, col_names = table_header) %>%
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mutate(timestamp = as_date(as_datetime(timestamp))) %>% # Formatting the date
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melt(id.vars = "timestamp", variable.name = "category", value.name = "amount") %>% # Formatting the table to plot each category
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ggplot(aes(x = timestamp, y = amount)) +
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21
plot/plot.r
Executable file
21
plot/plot.r
Executable file
@ -0,0 +1,21 @@
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#!/usr/bin/env Rscript
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# Libraries:
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library(reshape2)
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library(tidyverse)
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# Parsing command line arguments:
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options = commandArgs(trailingOnly = TRUE)
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filename = options[1]
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plot_type = options[2]
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table_header = options[-1:-2]
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read_csv(filename, col_names = table_header) %>%
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mutate(timestamp = as_date(as_datetime(timestamp))) %>% # Formatting the date
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melt(id.vars = "timestamp", variable.name = "category", value.name = "amount") %>% # Formatting the table to plot each category
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{
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if (plot_type == "bar")
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ggplot(data = ., aes(x = timestamp, y = amount, fill = category)) + geom_bar(stat = "identity")
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else if (plot_type == "line")
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ggplot(data = ., aes(x = timestamp, y = amount)) + geom_line(aes(color = category))
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}
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