39. Concat Pandas Series/DataFrames (Part 1) | Python Pandas Tutorial
The concat() method is used to concatenate pandas object (Series/DataFrames) along a particular axis (means Horizontally or Vertically).
axis=0,
ignore_index: bool = False,
join='outer',
keys=None,
names=None,
verify_integrity: bool = False,
sort: bool = False,
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Parameters
-----------------------------------
objs : a sequence or mapping of Series or DataFrame objects
------------------------------------
axis : {0/'index', 1/'columns'}, default 0
axis = 0 Vertically (row) [Default]
axis = 1 Horizontally (Column).
------------------------------------
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.
----------------------------------
The axis to concatenate along.
join : {'inner', 'outer'}, default 'outer'
Inner join only returns rows whose index is present in both data frames.
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axis = 0 Vertically (row) [Default]
axis = 1 Horizontally (Column).
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Dataframes
----------------------------------------------------
data1 = {'Name':['Priyang','Aadhya','Vedant','Parshv','krisha'],
'Marks':[98,99,89,85,87]
}
data2={'Name':['Rahul','Anil','Paresh'],
'Marks':[98,99,89]
}
df1=pd.DataFrame(data1)
df2=pd.DataFrame(data2)
df1
df2
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Github Link: https://github.com/PRIYANG-BHATT/Data...
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