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--- onlinedb [2022/03/09 11:19]
qcbs
+++ onlinedb [2025/04/08 14:34] (current)
qcbs [Exercise 3 - SELECT statement]
@@ Line 325: / Line 325: @@
 CREATE TABLE species (species_id INT NOT NULL, full_name varchar(255), short_name VARCHAR(100));
 COPY species FROM 'C:/bdlibre/species_acro.csv' WITH csv HEADER DELIMITER AS ',';
+</file>
+===== Exercise 3 - Importing data into SQLite in R =====
+First install the RSQLite package
+<file rsplus>
+install.packages('RSQLite')
+</file>
+To load it in R, you will need to load the DBI package
+<file rsplus>
+library(DBI)
+</file>
+Then, create the file containing the database
+<file rsplus>
+mydb <- dbConnect(RSQLite::SQLite(), "QCBS_Workshop.sqlite")
+</file>
+Set this to where you have downloaded the files
+<file>
+setwd('C:\\User\MyName\Workshop\')
+</file>
+You can now load the CSV files in R as data frames
+<file>
+lakes <- read.csv('lakes.csv')
+lakes_species <- read.csv('lakes_species.csv')
+species_acro <- read.csv('species_acro.csv')
+</file>
+And then load those dataframes into the database
+<file rsplus>
+dbWriteTable(mydb, "lakes", lakes)
+dbWriteTable(mydb, "lakes_species", lakes_species)
+dbWriteTable(mydb, "species_acro", species_acro)
+dbListTables(mydb)
+</file>
+You can then run most queries below with dbGetQuery. For example:
+<file rsplus>
+lake_prairies<-dbGetQuery(mydb, "SELECT * FROM lakes WHERE ecozone='Prairies'")
 </file>
 ===== REFERENCES =====
@@ Line 406: / Line 448: @@
 **Question 1** :?: -  How many lakes in British Columbia receive more than 3000 mm of precipitation (totp_ann column)?
-\\ ++answer| 12 ++ \\
+\\ ++answer| SELECT count(*) FROM lakes WHERE province='BRITISH COLUMBIA' AND totp_ann>3000; 12 ++ \\
-**Question 2** :?: -  What is the average Elevation (mean_ele column) of all lakes in the Montane Cordillera Ecozone (use the avg() operator)?
+**Question 2** :?: -  What is the average Elevation (mean_elev column) of all lakes in the Montane Cordillera Ecozones (use the avg() operator)?
-\\ ++answer| 1364.36 ++ \\
+\\ ++answer| SELECT avg(mean_elev) FROM lakes WHERE ecoprov LIKE '%Montane Cordillera'; 1364.36 ++ \\
 \\
-Note: the % operator is a wildcard used to replace the beginning or the end of a string.
+Note: the % operator is a wildcard used to replace the beginning or the end of a string in a query using LIKE.
 \\
 Select all lake names that contain the word 'Small'
@@ Line 429: / Line 471: @@
 **Question 3** :?: - What is the maximum latitude of all lakes in Ecozones with names that start with 'Taiga'
-\\ ++answer| 68.8 ++ \\
+\\ ++answer| SELECT max(latitude) FROM lakes WHERE ecozone like 'Taiga%'; 68.8 ++ \\
 **Question 4** :?: - How many species of Daphnia are there in the species table?
-\\ ++answer| 17 (21 have the word 'Daphnia' somewhere in their name) ++ \\
+\\ ++answer| SELECT count(*) FROM species_acro WHERE full_name like 'Daphnia%'; 17 (21 have the word 'Daphnia' somewhere in their name) ++ \\
 ===== Exercise 4 - GROUPING =====
@@ Line 451: / Line 493: @@
 **Question 5** :?: -  Which province has the lake with the highest maximum temperature (column tmax_ann)?
-\\ ++answer| BRITISH COLUMBIA 14.60 ++ \\
+\\ ++answer| SELECT province, max(tmax_ann) FROM lakes GROUP BY province ORDER BY max DESC LIMIT 1;
+BRITISH COLUMBIA 14.60 ++ \\
 Update statement:
@@ Line 671: / Line 714: @@
 lakes <- tbl(src, "lakes") # Define lakes table
 lakes_qc<-filter(lakes, province  %=% 'QUEBEC') # Select lakes in Quebec
-prov_tmean<-summarise(group_by(lakes, province), mean(tmean_an)) # Mean annual temperature per province
+prov_tmean<- lakes |> group_by(province) |> summarise(mean(tmean_an)) # Mean annual temperature per province
-prov_tmean=collect(prov_tmean) # Transfer result to standard R data frame
+prov_tmean <- collect(prov_tmean) # Transfer result to standard R data frame
-lakes_qc2<-tbl(src, sql("SELECT * FROM lakes WHERE province='QUEBEC'")) #Perform any SQL statement
+lakes_qc2 <- tbl(src, sql("SELECT * FROM lakes WHERE province='QUEBEC'")) #Perform any SQL statement
 </file>