Convert dataframe into list

In this tutorial, we will learn how we can convert the dataframes into a simple Python list. We will learn about all the methods that we can use to convert dataframe into lists. Before proceeding with the methods, let’s have a look at what a dataframe is and how we can create a dataframe in Python using Panda.

Pandas Dataframe

The dataframes in the panda module is a 2-D (two-dimensional) size module that is potentially in the heterogeneous tabular data structure with its axes (row & columns), labelled with variables. In simple words, a data frame is a 2-D data structure in which the data is aligned in tabular form.

Creating a Dataframe in Pandas

We can create a basic dataframe by the following program using the Pandas module in Python:

Example –

Output:

      Famous Name     Age  0      Stark Iron             42  1   Captain Rogers       95  2     Hulk banner       38  3    Spidy Parker       18  

So, that’s how we can create a dataframe using the Panda module and after looking at the output, we can also figure out how a dataframe looks like.

Converting Dataframe into List

We will use the tolist() function from the Panda module in our program in the following way while converting the given dataframe into list:

Let’s use this function in an example to understand the working of the tolist() function.

Example:

Output:

[['Stark Iron', 42], ['Captain Rogers', 95], ['Hulk banner', 38], ['Spidy Parker', 18]]  

Methods to Convert Dataframe into List:

The dataframe can be converted into a Python list in many ways. In this section, we will discuss all the methods that we are going to use to convert a given dataframe into a list. Here, we will use the following four methods with the help of the tolist() function:

1. Converting dataframe while containing all rows
2. Converting dataframe into a nested list
3. Converting dataframe into a nested list of columns
4. Converting dataframe into a list with column names included

Now, let’s learn about each method with an example to understand them in a better way.

Method 1: Converting dataframe while containing all rows

In this method, we will convert a given dataframe into a list that will contain all the rows of a particular column from the dataframe.

Look at the following program to understand the implementation of this method:

Example –

Output:

['Stark Iron', 'Captain Rogers', 'Hulk banner', 'Spidy Parker']  

So, as we can see in the output that we have converted the famous name column of defined dataframe into a single list and printed it in the output.

Method 2: Converting dataframe into a nested list

In this method, we will convert the given dataframe into a nested list that will contain all the rows of all the columns from the dataframe separately.

We will use this method in the following example to understand its implementation:

Example –

Output:

[['Stark Iron', 'Captain Rogers', 'Hulk banner', 'Spidy Parker'], [42, 95, 38, 18]]  

Method 3: Converting dataframe into a nested list of columns

Under this method, we will be converting a given dataframe into a list that will contain multiple lists in it that are having all the columns of a row.

Look at the following program to understand the implementation of this method:

Example –

Output:

[['Stark Iron', 42], ['Captain Rogers', 95], ['Hulk banner', 38], ['Spidy Parker', 18]]  

That’s how we can use this method to convert the given dataframe into a list containing multiple lists of having data from all columns and rows.

Method 4: Converting dataframe into list with column names included

We use this method when we want to convert the given dataframe into a list that contains multiple lists having all the columns with column names of dataframe along with rows.

We will use this method in the following example to understand its implementation:

Example –

Output:

[['Famous Name', 'Age'], ['Stark Iron', 42], ['Captain Rogers', 95], ['Hulk banner', 38], ['Spidy Parker', 18]]  

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