What are ways to combine dataframes in Python?
In Python, especially with the pandas library, we have multiple methods to combine data frames. Here are some common approaches:1. Using FunctionThe function is used to concatenate two or more data frames either vertically or horizontally. For example, if we have two data frames and , we can merge them vertically (increasing the number of rows) as follows:To merge them horizontally (increasing the number of columns), use the parameter:2. Using FunctionThe function combines two data frames based on one or more key columns, similar to SQL JOIN operations. For example, if both data frames contain a common column , we can merge them on this column:Additionally, the function allows specifying the merge type using the parameter, which can be , , , or . The default is .3. Using FunctionThe function is a simplified version of for merging on indices. If the data frames' indices contain key information, we can use to combine them:The function defaults to a left join, but we can specify different join types using the parameter, such as , , , or .Example:Suppose we have two data frames: one containing customer basic information and another containing customer purchase records. We can merge them using to facilitate further analysis:This will output the merged data frame, which includes the customer ID, name, and their order information.By using these methods, we can flexibly handle and analyze data from different sources, effectively supporting data analysis and machine learning projects.