41. Concat Pandas DataFrames (Part 3) | Python Pandas Tutorial

The concat() method is used to concatenate pandas object (Series/DataFrames) along a particular axis (means Horizontally or Vertically).
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axis=0,
ignore_index: bool = False,
join='outer',
keys=None,
names=None,
verify_integrity: bool = False,
sort: bool = False,
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Parameters
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obj : a sequence or mapping of Series or DataFrame objects
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axis : {0/'index', 1/'columns'}, default 0
- axis = 0 Vertically (row) [Default]

- axis = 1 Horizontally (Column).
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ignore_index: bool, default False
- If True, do not use the index values along the concatenation axis.
- The resulting axis will be labeled 0, ..., n - 1.
- This is useful if you are concatenating objects where the concatenation axis does not have meaningful indexing information.
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The axis to concatenate along.
join : {'inner', 'outer'}, default 'outer'
- Inner join only returns rows whose index is present in both dataframes.
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- axis = 0 Vertically (row) [Default]

- axis = 1 Horizontally (Column).
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keys: sequence, default None
- Construct hierarchical index using the passed keys as the outermost level.
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names: list, default None
- Names for the levels in the resulting hierarchical index.
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verify_integrity : bool, default False
- Check whether the new concatenated axis contains duplicates.
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sort: bool, default False
- Sort non-concatenation axis if it is not already aligned when 'join' is 'outer'.
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(Sort Columns if you are adding rows,
Sort Rows if You are adding Columns)
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- This has no effect when join='inner' , which already preserves the order of the non-concatenation axis.

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[shadyelsherif]

Thanks a lot sir for this great effort.
I have finished the full series
from scratch, but do you think it's enough for learning pandas and now I'm ready to create projects by using it and find a job?