pandas’s library allows two series to be stacked as vertical and horizontal using a built-in command called concat()
. This action is usually performed to create a dataframe from two series.
pandas.concat(objs, axis, join, ignore_index,keys, levels, names, verify_integrity,sort, copy)
objs
: This is the mapping of Dataframe or Series objects.
If we pass the mapping, their keys will be sorted and used in argument keys
. If keys
are already passed as an argument, then those passed values will be used. Any Null
objects will be dropped.
axis
: This is the axis along which we want to stack our series. The default is 0
.
0
represents Horizontal.
1
represents Vertical.
join
: This parameter tells us how to handle indexes on other axes. It has two types: inner
and outer
, and the default is outer
.
ignore_index
(bool): This tells whether or not to ignore index values. The default is False
.
keys
(sequence): This tells us the sequence of the identifier in resultant indices. The default is None
.
levels
(list of sequences): This tells us the levels for constructing Multi-index. The default is None
.
names
(list): This tells us the names of levels in resultant index. The default is None
.
verify_integrity
(bool): This checks duplicates in the resultant axis. The default is False
.
sort
(bool): This sorts non-concatenation axis. It only works with outer
join, and the default is False
.
copy
(bool): This tells whether or not to stop copying unnecessary data. The default is True
.
Series: If objs
contains all series.
Dataframe: If objs
contains at least one Dataframe.
concat()
#importing pandas libraryimport pandas as pd#initializing two pandas seriesseries1 = pd.Series(range(len('educative')))series2 = pd.Series(list('educative'))#vertical stack with axis = 0 as parameterprint(pd.concat([series1, series2], axis = 0))
append()
#importing pandas libraryimport pandas as pd#initializing two pandas seriesseries1 = pd.Series(range(len('educative')))series2 = pd.Series(list('educative'))#Vertical stack using appendprint(series1.append(series2))
#importing pandas libraryimport pandas as pd#initializing two pandas seriesseries1 = pd.Series(range(len('educative')))series2 = pd.Series(list('educative'))#Horizontal stack with axis = 1 as parameterprint(pd.concat([series1, series2], axis = 1))