Subtracting COUNT results in SQLite - sqlite

In my SQLite query, I create two temp tables, both of which have a column with COUNT results. I then combine these two columns into a new table.
This part of the query works fine: I get the two columns of numbers in my new table.
I named these two columns using as C1 and as C2. But when I add a third calculated column containing the expression C1-C2, this third column contains only zeros.
How can I subtract the numbers using my column names?

How about?
SELECT c1, c2, (c1 - c2) as `difference` FROM table

Related

While Merging of data into one table I am getting duplicates

I have one table with 24,508 rows & other table with 92,860 rows. I want to merge two tables one table but I am getting more number of rows than 24,508. I am getting 26,260 rows.
I have used a unique column from both tables to merge it.
Merge(df1,df2,by.x=c("uniqueid"), by.y=c("uniqueid"), all.x=TRUE)

how to extract the lines that have equal values in a table between the different columns

I have a data table, where I would like to extract the rows that are equal in the different columns
what are the different functions to get there ?

dplyr mutate if else

I need help to find the best way to convert the table below using the conditions:
If...
the data of the 1st column (plot number) and
the data of the 2st column (subplot number) and
the data of the 3rd column (trees) and
the name of the tree in the 4th column (tree_species) and
the data of the 5th column (stems)
are the SAME in different rows the new column dbh_equivalent will be result of the function:
=SQRT(dbc_cm - row1^2+dbc_cm-row2^2+...+dbc_cm- row n^2).
That is, in the table above the result would be:
Thanks

Data Comparison in R

I am trying to compare two Excel files (same number of columns, but sometimes different number of rows).
I imported the Excel files to data1 and data2 respectively.
library(dataCompareR)
comparedata <- rCompare(data1, data2)
summary(comparedata)
saveReport(comparedata, reportName = 'Comparison Result')
All goes well, but I have three challenges:
The Sample row data is set to 5. How can I increase that to the actual different row that the summery comes up with?
How can I ask the primary key in the result as it only shows the two matching columns?
Sometimes the numbers of the row don't match, and the data gets off. Can I set up a primary comparison key instead of row to row?

Spotfire Merging Tables - Preserving Order

I am attempting to add a column from one table to another. I can't use a simple join because the data type of the column changes, so I am using a data function/r-script to add the specified column.
I can get the proper column to populate, but cannot get the order to preserve (i.e. the incorrect records are being returned for a given identifier PROPNUM).
# join tables to ensure proper number of records
newTable <- merge(OutputTable, InputTable, by = "PROPNUM")
#populate column with values from merged table
OutputColumn <- newtTable[,4]
#sample output - output column is not order preserved
PROPNUM OutputColumn
A B
A B
C A
C A
B C
B C
If you want the order to be as the input table
# sort newtable
newTable <- newTable(order(newTable$column1, newTable$column2, newTable$....))
Merging (or joining) does not preserve the input orders.

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