What is the syntax for pandas concat?

What is the pandas concat Syntax?

Pandas is a powerful open-source Python library designed to help data scientists and developers quickly and effectively manipulate, analyze, and visualize data for higher productivity and deeper insights. The pandas concat syntax is an important technique for combining multiple DataFrames or Series into a single object. It gives users the ability to combine data from different sources by adding additional rows or columns to existing DataFrames.

The general syntax for the pandas concat method is as follows:

pd.concat(objs, axis=0, join='outer', ignore_index=False, keys=None)

The parameters are defined as follows:

- objs: This is a list of Sequence objects or NumPy arrays that will be used to construct the new DataFrame.

- axis: This parameter specifies whether you want to concatenate along the rows (axis = 0) or columns (axis = 1). The default value is axis = 0.

- join: This determines how the two objects will be joined together, either through 'inner' which preserves only values that appear in both objects, or 'outer' which preserves all values from both objects. The default value is 'outer'.

- ignore_index: This parameter allows you to choose whether you want the original indexing from each of the objects preserved after concatenation. If set to False, a list of Sequences with their own indexes will be returned instead of a single DataFrame with reset indexes for each Sequence/array. The default value is False.

- keys: This parameter designates labels for each of the pieces that make up your new DataFrame after concatenation (from each array in your objs parameter). It should be a list with the same length as objs and it provides simple organization when inspecting your newly created DataFrame. The default value is None.