There are several approaches to resolve ambiguous rows when combining multiple tables:
Use aliases: When columns in different tables have the same name, use aliases to differentiate them. For example, if both tables have a column named "name," rename one of them to "table1name" and the other to "table2name."
Use JOIN conditions: Specify specific conditions to join the tables together, using columns that are distinct in each table. For example, if one table has a column named "ID" and the other has a column named "employeeID," join on those distinct columns.
Use subqueries or temporary tables: Use subqueries or temporary tables to break down the tables into smaller chunks, resolving any conflicts before combining them.
Use UNION instead of UNION ALL: Use UNION instead of UNION ALL to eliminate duplicate rows. UNION will remove any rows that appear in both tables, which can help to resolve ambiguities.
Change the data type: If columns have the same name but different data types, changing one of the data types can resolve the ambiguity. For example, if one table has a column named "age" that is an integer and the other has a column also named "age" that is a string, convert the string column to an integer before combining the tables.
Please start posting anonymously - your entry will be published after you log in or create a new account. This space is reserved only for answers. If you would like to engage in a discussion, please instead post a comment under the question or an answer that you would like to discuss
Asked: 2022-02-19 11:00:00 +0000
Seen: 13 times
Last updated: Oct 10 '22
Is it possible that there are some missing values when combining across columns?
How can a specific range of rows be combined and aligned to the left in Excel?
What is the process to sort the first 50 rows?
How can Bootstrap tables have several rows and columns?
How can I retrieve data.table groups that have a specific number of rows only?
What is an efficient way to complete missing rows in a pandas dataframe?
How can I fix the error where the replacement has 12 rows and the data only has 10?