How to Explode Multiple Columns in Pandas

In this article, we will see How to explode multiple columns in Pandas with the help of the example. The explode() method is the Pandas DataFrame method that is used to transform each element of a list into rows.

Throughout this article, we explore all Panda’s explode multiple columns with the help of different examples so that you can easily any question regarding the Python explode() function.

Before using explode(), we must know the Pandas explode() method and its parameters.

Let’s see.

Pandas explode() Method

It is a Pandas DataFrame method that is always used to transform each element of the list kike into rows and also replace index values.
explode() method returns a new DataFrame.

Parameters:

Pandas explode() method accepts two arguments:

• column:- Colume to be explode. It can be a single or a list of columns.
• ignore_index:- If it is True, the resulting index will be 0, 1, 2,…n-1

Let’s see some examples of Pandas explode list to rows.

Explode multiple columns in Pandas

To apply the Python Pandas explode() method we must have a Python DataFrame, let’s create a sample Pandas DataFrame.here I am using the Jupyter Notebook tool, You can use any tool at your convenience.

Use the below code to create a sample Pandas DataFrame.

from pandas import DataFrame

dictionary = [
        
        {
            "name": "Vishvajit",
            "gender": "Male",
            "age": 25,
            "skills": ["Python", "SQL", "AWS"]
           },
        
        {
            "name": "Vinay",
            "gender": "Male",
            "age": 20,
            "skills": ["Finance", "Accounting", "Excel"]
           },
        
        {
            "name": "Harshita",
            "gender": "Female",
            "age": 24,
            "skills": ["Graphics Design", "Video Editing"]
            
           }
]
df = DataFrame(data=dictionary)
print(df)

After executing the above code, The sample DataFrame will look like this.

        name  gender  age                            skills
0  Vishvajit    Male   25                [Python, SQL, AWS]
1      Vinay    Male   20      [Finance, Accounting, Excel]
2   Harshita  Female   24  [Graphics Design, Video Editing]

Now the requirement is to transform each item of the list in column skills into a separate row.

Let’s see how can we do that.

Example: Pandas explode list to rows

from pandas import DataFrame

dictionary = [
        
        {
            "name": "Vishvajit",
            "gender": "Male",
            "age": 25,
            "skills": ["Python", "SQL", "AWS"]
           },
        
        {
            "name": "Vinay",
            "gender": "Male",
            "age": 20,
            "skills": ["Finance", "Accounting", "Excel"]
           },
        
        {
            "name": "Harshita",
            "gender": "Female",
            "age": 24,
            "skills": ["Graphics Design", "Video Editing"]
            
           }
]
df = DataFrame(data=dictionary)
df = df.explode(['skills'])
print(df)

After applying the Pandas explode() method the output will be.

        name  gender  age           skills
0  Vishvajit    Male   25           Python
0  Vishvajit    Male   25              SQL
0  Vishvajit    Male   25              AWS
1      Vinay    Male   20          Finance
1      Vinay    Male   20       Accounting
1      Vinay    Male   20            Excel
2   Harshita  Female   24  Graphics Design
2   Harshita  Female   24    Video Editing

As you can see in the above output, the index number is the same for each item of the list for a particular employee but sometimes we want to unique index number for each row then we can use the second parameter of the explode() method which is ignore_index.

To define a unique index for each row, we have to pass True to ignore_index parameter.

Example: Explode a column in Pandas

from pandas import DataFrame

dictionary = [
        
        {
            "name": "Vishvajit",
            "gender": "Male",
            "age": 25,
            "skills": ["Python", "SQL", "AWS"]
           },
        
        {
            "name": "Vinay",
            "gender": "Male",
            "age": 20,
            "skills": ["Finance", "Accounting", "Excel"]
           },
        
        {
            "name": "Harshita",
            "gender": "Female",
            "age": 24,
            "skills": ["Graphics Design", "Video Editing"]
            
           }
]
df = DataFrame(data=dictionary)
df = df.explode(['skills'], ignore_index=True)
print(df)

The Output of the above code will be like this.

       name  gender  age           skills
0  Vishvajit    Male   25           Python
1  Vishvajit    Male   25              SQL
2  Vishvajit    Male   25              AWS
3      Vinay    Male   20          Finance
4      Vinay    Male   20       Accounting
5      Vinay    Male   20            Excel
6   Harshita  Female   24  Graphics Design
7   Harshita  Female   24    Video Editing

In all the above examples, we have seen the Pandas explode() method to explode the single column but sometimes we need to explode the multiple columns.

To explode multiple columns in Pandas, pass the column names as a list to the first parameter of the explode() method.

Note:- Length of the list must be the same in all the columns.

Let’s see an example.

Example: Explode multiple columns in Pandas

from pandas import DataFrame

dictionary = [
        
        {
            "name": "Vishvajit",
            "gender": "Male",
            "age": 25,
            "skills": ["Python", "SQL"],
            "course": ["BCA", "MCA"]
           },
        
        {
            "name": "Vinay",
            "gender": "Male",
            "age": 20,
            "skills": ["Accounting", "Excel"],
            "course": ["BCOM", "MCOM"]
           },
        
        {
            "name": "Harshita",
            "gender": "Female",
            "age": 24,
            "skills": ["Graphics Design", "Video Editing"],
            "course": ["BCA", "MCA"]
            
           }
]
df = DataFrame(data=dictionary)
df = df.explode(['skills', 'course'], ignore_index=True)
df

After exploring the multiple columns the output will be:

        name  gender  age           skills course
0  Vishvajit    Male   25           Python    BCA
1  Vishvajit    Male   25              SQL    MCA
2      Vinay    Male   20       Accounting   BCOM
3      Vinay    Male   20            Excel   MCOM
4   Harshita  Female   24  Graphics Design    BCA
5   Harshita  Female   24    Video Editing    MCA

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Conclusion

Throughout this article, we have seen the Pandas explode() method to explode the single and multiple columns with the examples. There is a high chance in the coding interview, This question might be asked by the interviewer if you are going for a data engineering, or data analyst job profile or even for a Python developer job profile.

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