Convert List to dataframe in Python

Python List Dataframe Conversion

In this guide, we’ll learn how to take use of Python’s list comprehension and transform it into a dataframe.

But before we get started, let’s go through what the list is and what dataframes are.

In Python, a list is a data structure whose items are denoted by square brackets.

A list as an illustration

is-

Data frames are the rows and columns that make up a data table.

Importing pandas allows for their utilization.

Let’s have a look at the many ways we may transform that list into a dataframe in

Python.

1. Using
   
   DataFrame()
   
2. Using list with index and column names
3. Using zip()
4. Using Multidimensional list
5. Using multidimensional list with column and data type
6. Using lists in the dictionary

Using pd.DataFrame()

In the first method, we have utilized the pd.DataFrame() function to transform a list into a data frame.

The following code demonstrates how it is

done-

Product Code:

                0
0         English
1           Hindi
2     Mathematics
3         Science
4  Social Science

Clarification:

Now let’s have a look at why the aforementioned happened.

program-

1. In the first step we have imported the pandas library.
2. After this, we have declared the list that has strings as its values.
3. Finally, we have passed this list in
   
   DataFrame()
   
   and displayed the output.

Using List with Index and Column Names

Method two involves the construction of a dataframe with a specified index value and a named column.

The code sample provided here demonstrates

same.

Resulting

:

Explanation:

           Subjects
i           English
ii            Hindi
iii     Mathematics
iv          Science
v    Social Science

Let’s break down the aforementioned, shall we?

program-

1. In the first step we have imported the pandas library.
2. After this, we have declared the list that has strings as it’s values.
3. Finally, we have passed this list in
   
   DataFrame()
   
   with a list of index values and the column name.
4. On executing the program, it displays the desired output.

Using zip()

Here, we make use of the zip format ().

The following code demonstrates how it is

done-

Resulting

Explanation:

         Subjects    Code
0         English       20
1           Hindi          21
2     Mathematics    22
3         Science          23
4  Social Science      24

Now let’s have a look at why the aforementioned happened.

program-

1. In the first step, we have imported the pandas library.
2. After this, we have declared the list that has strings as its values and another list contains the index values.
3. Finally, we have passed the
   
   list_values
   
   and
   
   list_index
   
   in zip inside
   
   DataFrame()
   
   with a list of index values and the column name.
4. On executing the program, it displays the desired output.

Using Multidimensional List

We’ll examine the usage of a multidimensional list in a transformational context.

The code provided here is an example of

same.

Resulting

:

Subject Name  Subject Code
0      English          4101
1        Hindi          4102
2      Science          4103
3  Mathematics          4104
4     Computer          4105

Clarification:

The moment has come to comprehend the aforementioned.

program-

1. In the first step we have imported the pandas library.
2. After this, we have declared the list contains different lists and each list has a string and an integer value.
3. Finally, we have passed the list_values in pd.DataFrame() with a list of column names.
4. On executing the program, it displays the desired output.

Using Multidimensional List with Column and Data Type

In this method, the preceding protocol will be slightly modified.

The following code demonstrates how it is

done-

Resulting

Explanation:

         First_Name  Last_Name   Age
0      Colin                  Lassiter      46.0
1      James                Gomez       24.0
2       Sara                  Charles      34.0
3      Raven                Stewart      24.0
4     Oliver                 Osment      21.0

Now let’s have a look at why the aforementioned happened.

program-

1. In the first step, we have imported the pandas library.
2. After this, we have declared the list contains different lists and each list has two string
   
   values(first name and last name)
   
   and an integer
   
   value(age).
   
3. Finally, we have passed the
   
   list_values
   
   in
   
   DataFrame()
   
   with a list of column names and the data type.
4. On executing the program, it displays the desired output.

Using Lists in the Dictionary

In the final approach, we’ll merge lists and dictionaries by turning the list into a dataframe.

The code provided here is an example of

same.

Resulting

:

Explanation:

       First Name   Last_Name    Age
0      Colin               Lassiter         46
1      James            Gomez           24
2       Sara              Charles           34
3      Raven            Stewart          24
4     Oliver             Osment          21

The moment has come to comprehend the aforementioned.

program-

1. In the first step, we have imported the pandas library.
2. After this, we have declared three lists, namely f_name, l_name, and age.
3. In the next step, we have used these lists as values for the keys of the dictionary.
4. Finally, we have passed dict in
   
   DataFrame().
   
5. On executing the program, it displays the desired output.