Hi Phillip,
Skipping to the last few lines of your email, did you download a
program to look at Sqlite databases (independent of R) as listed
below? Maybe that program ("DB Browser for SQLite") and/or the
instructions below can help you locate your database directory:
https://datacarpentry.org/semester-biology/computer-setup/
https://datacarpentry.org/semester-biology/materials/sql-for-dplyr-users/
If you do have that program, and you're still seeing an error, you
might consider looking for similar issues at the appropriate
'datacarpentry' repository on Github (or posting a new issue
yourself):
https://github.com/datacarpentry/R-ecology-lesson/issues
Finally, I really feel you'll benefit from reading over the documents
pertaining to "R Data Import/Export" on the www.r-project.org website.
No disrespect to the people at 'datacarpentry', but you'll find
similar (and possibly, easier) R code to follow at section 4.3.1
'Packages using DBI' :
https://cran.r-project.org/doc/manuals/r-release/R-data.html
HTH, Bill.
W. Michels, Ph.D.
On Fri, Jan 10, 2020 at 10:32 AM Phillip Heinrich <herd_...@cox.net> wrote:
>
> Working my way through a tutorial named Data Carpentry
> (https://datacarpentry.org/R-ecology-lesson/). for the most part it is
> excellent but I’m stuck on the very last section
> (https://datacarpentry.org/R-ecology-lesson/05-r-and-databases.html).
>
> First, below are the packages I have loaded:
> [1] "forcats" "stringr" "purrr" "readr" "tidyr" "tibble"
> "ggplot2" "tidyverse" "dbplyr" "RMySQL" "DBI"
> [12] "dplyr" "RSQLite" "stats" "graphics" "grDevices" "utils"
> "datasets" "methods" "base"
>
>
> >
>
>
> Second,
> Second, is the text of the last section of the last chapter titled “Creating
> a New SQLite Database”.
> Second, below is the text from the tutorial. The black type is from the
> tutorial. The green and blue is the suggested R code. My comments are in
> red.
> Creating a new SQLite database
> So far, we have used a previously prepared SQLite database. But we can also
> use R to create a new database, e.g. from existing csv files. Let’s recreate
> the mammals database that we’ve been working with, in R. First let’s download
> and read in the csv files. We’ll import tidyverse to gain access to the
> read_csv() function.
>
> download.file("https://ndownloader.figshare.com/files/3299483";,
> "data_raw/species.csv")
> download.file("https://ndownloader.figshare.com/files/10717177";,
> "data_raw/surveys.csv")
> download.file("https://ndownloader.figshare.com/files/3299474";,
> "data_raw/plots.csv")
> library(tidyverse)
> species <- read_csv("data_raw/species.csv")No problem here. I’m pulling
> three databases from the Web and saving them to a folder on my hard drive.
> (...data_raw/species.csv) etc.surveys <- read_csv("data_raw/surveys.csv")
> plots <- read_csv("data_raw/plots.csv")Again no problem. I’m just creating
> an R data files. But here is where I loose it. I’m creating something named
> my_db_file from another file named portal-database-output with an sqlite
> extension and then creating my_db from the My_db_file. Not sure where the
> sqlite extension file came from. Creating a new SQLite database with dplyr is
> easy. You can re-use the same command we used above to open an existing
> .sqlite file. The create = TRUE argument instructs R to create a new, empty
> database instead.
>
> Caution: When create = TRUE is added, any existing database at the same
> location is overwritten without warning.
>
> my_db_file <- "data/portal-database-output.sqlite"
> my_db <- src_sqlite(my_db_file, create = TRUE)Currently, our new database is
> empty, it doesn’t contain any tables:
>
> my_db#> src: sqlite 3.29.0 [data/portal-database-output.sqlite]
> #> tbls:To add tables, we copy the existing data.frames into the database one
> by one:
>
> copy_to(my_db, surveys)
> copy_to(my_db, plots)
> my_dbI can follow the directions to fill in my_db but I have no idea how to
> access the tables. The text from the tutorial below says to check the
> location of our database. Huh! Can someone give me some direction. Thanks.
>
>
>
>
>
> If you check the location of our database you’ll see that data is
> automatically being written to disk. R and dplyr not only provide easy ways
> to query existing databases, they also allows you to easily create your own
> databases from flat files!
>
>
>
> Here is where I loose it.
>
>
> [[alternative HTML version deleted]]
>
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