Pandas Concatenate Data Frames [2021]

Pandas Concatenate Data Frames [2021]

Ever wondered how to concatenate two data frames in Python. Look no further, find the details of the various functions available in Pandas to combine data frames. what you are looking for is here

Imagine you are having two sets of data that you have to combine to perform analysis. While using SQL, records from two or more tables in a database can be combined using SQL joins. Similarly, there are options in Python as well to concatenate data frames. So what is a data frame? A data frame in Python has multiple rows and columns. It is similar to a table in SQL. You have the pandas software library for data analysis in Python. Pandas concatenate data frames help us to combine data frames based on a certain logic. 

The different ways of combining data frames:

  • Inner Join: Inner join is quite akin to the intersection of two sets. In case of an inner join, a data frame is returned containing only those rows having common properties. Thus each row in the two combined data frames should have matching column values.
  • Left Join: A left join returns all rows from the left data frame and only the matching rows from the right data frame. 
  • Right Join: A right join returns all rows from the right data frame and only the matching rows from the left data frame. 
  • Full or Outer Join: A full join keeps all the rows from both the left data frame and the right data frame.

 Source

Let us now look at the functions present in Pandas to combine data frames or series.

data science dataframe pandas

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