What are the different options for merging DataFrames in Pandas?
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What are the different options for merging DataFrames in Pandas?
In Pandas, you can merge DataFrames using the merge() function. The main options include 'inner', 'outer', 'left', and 'right' joins.
Can you explain what each of these join types means?
Sure! An 'inner' join returns only the rows with matching keys in both DataFrames. An 'outer' join returns all rows from both DataFrames, filling in NaNs where there are no matches. A 'left' join returns all rows from the left DataFrame and matched rows from the right, while a 'right' join does the opposite.
How do I specify the keys to merge on?
You can specify the keys using the on parameter in the merge() function. If the keys have different names in the two DataFrames, you can use left_on and right_on.
Can I merge on multiple keys?
Yes, you can merge on multiple keys by passing a list of column names to the on, left_on, or right_on parameters.
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