Table of Contents
Pandas concat() function syntax
The pandas concat() function is used to join multiple pandas data structures along a specified axis and possibly perform union or intersection operations along other axes.
The following command explains the concat function:
concat(objs, axis=0, , join='outer', join_axes=None, ignore_index=False, keys=None, levels=None, names=None, verify_integrity=False)
Parameters:
The elements of the concat function can be summarized as follows:
- The
objs
function: A list or dictionary of Series, DataFrame, or Panel objects to be concatenated. - The
axis
function: The axis along which the concatenation should be performed. 0 is the default value. - The
join
function: The type of join to perform when handling indexes on other axes. The 'outer' function is the default. - The
join_axes
function: This is used to specify exact indexes for the remaining indexes instead of doing an outer/inner join. - The
keys
function: This specifies a list of keys to be used to construct a MultiIndex.
What are we going to cover?
We will discuss the following scenarios using pandas contact()
function
- Concatenate two Series with
default parameters
- Concatenate two Series
horizontally
- Concatenate two Series with
ignore_index
- Concatenate two Series with
axis-0
- Concatenate two DataFrames with
default parameters
- Concatenate two DataFrames
horizontally
- Concatenate two DataFrames with
ignore_index
- Concatenate two DataFrames with
axis-0
Scenario-1: Concatenate two Series with default parameters
Here we are going to concat two series with no parameters
Example: In this example, we created two series and concat two series with no parameters
# import pandas
import pandas
# creating the Series-1
data1 = pandas.Series([10,20,30,50,60])
# creating the Series-2
data2 = pandas.Series(['Python','java','html','php','R'])
#display two series
print(data1,data2)
print()
# concate two series
print(pandas.concat([data1, data2]))
Output:
0 10
1 20
2 30
3 50
4 60
dtype: int64 0 Python
1 java
2 html
3 php
4 R
dtype: object
0 10
1 20
2 30
3 50
4 60
0 Python
1 java
2 html
3 php
4 R
dtype: object
Scenario-2: Concatenate two Series horizontally
Here we are going to concat two series horizontally by setting axis parameter to 1
.
Example: In this example, we created two series and concat two series horizontally by setting axis parameter to 1
.
# import pandas
import pandas
# creating the Series-1
data1 = pandas.Series([10,20,30,50,60])
# creating the Series-2
data2 = pandas.Series(['Python','java','html','php','R'])
#display two series
print(data1,data2)
print()
# concate two series
print(pandas.concat([data1, data2],axis=1))
Output:
0 10
1 20
2 30
3 50
4 60
dtype: int64 0 Python
1 java
2 html
3 php
4 R
dtype: object
0 1
0 10 Python
1 20 java
2 30 html
3 50 php
4 60 R
Scenario-3: Concatenate two Series with ignore_index
Here we are going to concat two series horizontally by setting index
parameter to True
and False
Example 1: In this example, we are going to concat two series horizontally by setting index
parameter to True
# import pandas
import pandas
# creating the Series-1
data1 = pandas.Series([10,20,30,50,60])
# creating the Series-2
data2 = pandas.Series(['Python','java','html','php','R'])
#display two series
print(data1,data2)
print()
# concate two series
print(pandas.concat([data1, data2],ignore_index=True))
Output:
0 10
1 20
2 30
3 50
4 60
dtype: int64 0 Python
1 java
2 html
3 php
4 R
dtype: object
0 10
1 20
2 30
3 50
4 60
5 Python
6 java
7 html
8 php
9 R
dtype: object
Example 2: In this example, we are going to concat two series horizontally by setting index
parameter to False
# import pandas
import pandas
# creating the Series-1
data1 = pandas.Series([10,20,30,50,60])
# creating the Series-2
data2 = pandas.Series(['Python','java','html','php','R'])
#display two series
print(data1,data2)
print()
# concate two series
print(pandas.concat([data1, data2],ignore_index=False))
Output:
0 10
1 20
2 30
3 50
4 60
dtype: int64 0 Python
1 java
2 html
3 php
4 R
dtype: object
0 10
1 20
2 30
3 50
4 60
0 Python
1 java
2 html
3 php
4 R
dtype: object
dtype: object
Scenario-4: Concatenate two Series with axis-0
Here we are going to concat two series with axis = 0
Example: In this example, we are going to concat two series with axis = 0
# import pandas
import pandas
# creating the Series-1
data1 = pandas.Series([10,20,30,50,60])
# creating the Series-2
data2 = pandas.Series(['Python','java','html','php','R'])
#display two series
print(data1,data2)
print()
# concate two series
print(pandas.concat([data1, data2],axis=0))
Output:
0 10
1 20
2 30
3 50
4 60
dtype: int64 0 Python
1 java
2 html
3 php
4 R
dtype: object
0 10
1 20
2 30
3 50
4 60
0 Python
1 java
2 html
3 php
4 R
dtype: object
Scenario-5: Concatenate two DataFrames with default parameters
Here we are going to concat two dataframes with no parameters
Example: In this example, we are going to concat two dataframes with no parameters.
# import pandas
import pandas
# creating the dataframe -1
data1 = pandas.DataFrame([10,20,30,50,60])
# creating the dataframe-2
data2 = pandas.DataFrame(['Python','java','html','php','R'])
#display two DataFrames
print(data1)
print(data2)
print()
# concate two DataFrame
print(pandas.concat([data1, data2]))
Output:
0
0 10
1 20
2 30
3 50
4 60
0
0 Python
1 java
2 html
3 php
4 R
0
0 10
1 20
2 30
3 50
4 60
0 Python
1 java
2 html
3 php
4 R
Scenario-6: Concatenate two DataFrames horizontally
Here we are going to concat two dataframes horizontally
by specifying axis = 1
Example: In this example, we are going to concat two dataframes horizontally
by specifying axis = 1
# import pandas
import pandas
# creating the dataframe -1
data1 = pandas.DataFrame([10,20,30,50,60])
# creating the dataframe-2
data2 = pandas.DataFrame(['Python','java','html','php','R'])
#display two DataFrames
print(data1)
print(data2)
print()
# concate two DataFrame
print(pandas.concat([data1, data2],axis=1))
Output:
0
0 10
1 20
2 30
3 50
4 60
0
0 Python
1 java
2 html
3 php
4 R
0 0
0 10 Python
1 20 java
2 30 html
3 50 php
4 60 R
Scenario-7: Concatenate two DataFrames with ignore_index
Here we are going to concat two dataframes with ignore_index
parameter
Example 1: In this example, we are going to concat two dataframes with ignore_index
parameter sets to True
# import pandas
import pandas
# creating the dataframe -1
data1 = pandas.DataFrame([10,20,30,50,60])
# creating the dataframe-2
data2 = pandas.DataFrame(['Python','java','html','php','R'])
#display two DataFrames
print(data1)
print(data2)
print()
# concate two DataFrame
print(pandas.concat([data1, data2],ignore_index=True))
Output:
0
0 10
1 20
2 30
3 50
4 60
0
0 Python
1 java
2 html
3 php
4 R
0
0 10
1 20
2 30
3 50
4 60
5 Python
6 java
7 html
8 php
9 R
Example 2: In this example, we are going to concat two dataframes with ignore_index
parameter sets to False
# import pandas
import pandas
# creating the dataframe -1
data1 = pandas.DataFrame([10,20,30,50,60])
# creating the dataframe-2
data2 = pandas.DataFrame(['Python','java','html','php','R'])
# display two DataFrames
print(data1)
print(data2)
print()
# concate two DataFrame
print(pandas.concat([data1, data2],ignore_index=False))
Output:
0
0 10
1 20
2 30
3 50
4 60
0
0 Python
1 java
2 html
3 php
4 R
0
0 10
1 20
2 30
3 50
4 60
0 Python
1 java
2 html
3 php
4 R
Scenario-8: Concatenate two DataFrames with axis-0
Here we are going to concat two dataframes with axis-0
Example: In this example, we are going to concat two dataframes with axis-0
# import pandas
import pandas
# creating the dataframe -1
data1 = pandas.DataFrame([10,20,30,50,60])
# creating the dataframe-2
data2 = pandas.DataFrame(['Python','java','html','php','R'])
#display two DataFrames
print(data1)
print(data2)
print()
# concate two DataFrame
print(pandas.concat([data1, data2],axis=0))
Output:
0
0 10
1 20
2 30
3 50
4 60
0
0 Python
1 java
2 html
3 php
4 R
0
0 10
1 20
2 30
3 50
4 60
0 Python
1 java
2 html
3 php
4 R
Scenario-9: Perform inner and outer join with concat() function
Example: In this example, we are performing inner and outer join on the two dataframes.
# import pandas
import pandas
# creating the dataframe -1
data1 = pandas.DataFrame([10,20,30,50,60])
# creating the dataframe-2
data2 = pandas.DataFrame(['Python','java','html','php','R'])
# concate two DataFrame
print(pandas.concat([data1, data2],join='outer',axis=1))
# concate two DataFrame
print(pandas.concat([data1, data2],join='inner',axis=1))
Output:
0 0
0 10 Python
1 20 java
2 30 html
3 50 php
4 60 R
0 0
0 10 Python
1 20 java
2 30 html
3 50 php
4 60 R
Summary
In this tutorial we discussed how to concat Series
and DataFrame
in pandas using concat()
function, By considering all the parameters we concluded this tutorial.
References