Data Science Asked by nyoung4 on October 3, 2021
I want to track the nutritional value of different flours over time. What I got so far is a
data table like this:
|------------|------------|------------|------------|
| Flour | Date | Energy | Sugar |
|------------|------------|------------|------------|
| type 1 | 03/20 | 310 | 2 |
| type 2 | 03/20 | 290 | 1.8 |
| type 1 | 04/20 | 310 | 2.1 |
| type 2 | 04/20 | 287 | 1.7 |
Over time, I will add more nutritional values for the flours already in the table and
might add more types of flour. I might also want to add additional columns e.g. for protein.
The nutritional values of the different flour types should then be plotted over time
like this:
Energy
|
| * * * type 1
| # # type 2
| #
|
|-----------------------Date
03/20 04/20
What are the best tools to implement such a project?
My constraints are that I only want to use free and open-source software which runs under Arch Linux and that that i can export the plots
I would recommend the Python libraries: matplotlib and seaborn for generating and exporting static plots, or Plotly for interactive plots with hover features that you can export to a web browser.
Answered by Derek O on October 3, 2021
I suggest R. It allows for easy data handling including a good GUI (RStudio) and high-quality plotting tools (e.g. ggplot2
).
df = data.frame(c(1,2,3,4,3,4,8,6,2,3),c(5,4,3,6,5,4,2,6,7,8),c(1,2,3,4,5,6,7,8,9,10))
colnames(df)<-c("a","b","c")
df
library(reshape)
df2 = melt(data = df, measure.vars = c("a", "b"))
library(ggplot2)
ggplot(df2, aes(x = c, y = value, colour = variable)) +
geom_smooth() + geom_point() +
xlab("My x") + ylab("My y") +
ggtitle("My ggplot") +
labs(color='Type')
Answered by Peter on October 3, 2021
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