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)             

# Parameters

1. **`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.

2. **`axis`**: This is the axis along which we want to stack our series. The default is `0`.

   `0` represents *Horizontal*. 

   `1` represents *Vertical*. 

3. **`join`**: This parameter tells us how to handle indexes on other axes. It has two types: `inner` and `outer`, and the default is `outer`.

4. **`ignore_index` (bool)**: This tells whether or not to ignore index values. The default is `False`.

5. **`keys`(sequence)**: This tells us the sequence of the identifier in resultant indices. The default is `None`.

6. **`levels` (list of sequences)**: This tells us the levels for constructing Multi-index. The default is `None`.

7. **`names` (list)**: This tells us the names of levels in resultant index. The default is `None`.

8. **`verify_integrity` (bool)**: This checks duplicates in the resultant axis. The default is `False`.

9. **`sort` (bool)**: This sorts non-concatenation axis. It only works with `outer` join, and the default is `False`.

10. **`copy` (bool)**: This tells whether or not to stop copying unnecessary data. The default is `True`.

# Return values

 - **Series**: If `objs` contains all series.

 - **Dataframe**: If `objs` contains at least one Dataframe.

#importing pandas library
import pandas as pd

#initializing two pandas series
series1 = pd.Series(range(len('educative')))
series2 = pd.Series(list('educative'))

#vertical stack with axis = 0 as parameter
print(pd.concat([series1, series2], axis = 0))


#importing pandas library
import pandas as pd

#initializing two pandas series
series1 = pd.Series(range(len('educative')))
series2 = pd.Series(list('educative'))

#Vertical stack using append
print(series1.append(series2))


#importing pandas library
import pandas as pd

#initializing two pandas series
series1 = pd.Series(range(len('educative')))
series2 = pd.Series(list('educative'))

#Horizontal stack with axis = 1 as parameter
print(pd.concat([series1, series2], axis = 1))


How to stack two series vertically and horizontally in pandas

Use pandas's concat() to stack two series vertically or horizontally, creating a dataframe.

How to stack two series vertically and horizontally in pandas

Syntax

Parameters

Return values

Vertical stacking

Using `concat()`

Using `append()`

Horizontal stacking

How to stack two series vertically and horizontally in pandas

Syntax

Parameters

Return values

Vertical stacking

Using concat()

Using append()

Horizontal stacking

Using `concat()`

Using `append()`