6 Ways To Convert List To Dataframe In Python

list to dataframe

In your journey of learning computer programming, you might have come across plenty of topics in various programming languages like C, C++, Java, Python, etc. In the same way, have you come across the topic “Lists in Python” while you are learning a Python programming language? Do you know how to convert a list to dataframe in Python? Of course, you might have learned or you haven’t heard about it anytime.

Anyways, today, I am here to introduce you to a few ways to convert a list into a data frame in the Python Programming language. So, are you ready to begin? Consider this is another day in your journey of learning computer programming and try to read this article till the end.

Before going to start the topic, with your permission I would like to ask you a question related to this. Do you know what is a list in python and why it is needed to convert a list into a data frame? You need to know the answer to this question because without knowing this thing, your effort to learn this topic will be put in vain. Because no doctor will treat a patient without knowing his disease, similarly, no one will directly search for a solution without knowing the problem. Hence, you must know the need of converting a list into a data frame in the Python programming language. So, I would like to start the topic with this part.

Let us first discuss a few things about a list and a data frame in the Python programming language.

An ordered data structure that consists of elements separated by a comma within square brackets is known as a list in Python. Generally in Python, we use lists to store multiple items in a single variable.

And when it is coming to a DataFrame, it is a 2-dimensional labeled data structure consisting of some columns. These columns are of different types. A data frame in Python is like a spreadsheet or SQL table, or a dict of Series objects. In general, you will use a data frame most commonly as a pandas object.

Generally, you will use a data frame to store the data tables. In the data frame, the vectors are of equal length. It is known as a data type in a python programming language. You can construct this data type with multiple values in a structure.

Difference Between List and Dataframe

You can define a data frame by using parameters. Whereas the lists in python are limited by structure. This is the major difference between a list and a data frame in Python. DataFrames seem to be like generic data objects of R. You can use them to store the tabular data as they are two-dimensional, heterogeneous data structures.

The software library used for data manipulation and analysis in the Python programming language is known as the Pandas library. You can create a Pandas DataFrame using the lists, dictionary, and from a list of dictionaries, etc. As you know earlier, a Dataframe is a two-dimensional data structure where the data is arranged in a tabular form in rows and columns.

Convert List to Dataframe

Now, let us see how to convert a list into data fame in the Python programming language.

There are various methods to be followed to convert a list into a data frame in Python. I am going to introduce all those methods to you with the help of examples.

Method-1:

The first method you will use to convert a list to dataframe pandas is the basic and simplest approach. Let me show you the process to implement your program code. First, go to the windows search bar and open Spyder IDE from the Windows search bar, then you need to create a new file to write Dataframe creation code into it. Then, you will start writing your program code. Here you need to import panda’s module and then try to create a list of strings and then add the required items to it. Then you have to call the data frame constructor to pass your list as an argument. Now, you need to assign the data frame constructor to a variable.

Hence you have successfully created your data frame code file. Now, it’s time to save your file with the “.py” extension.

Let us see an example of this method.

Example-1:

import pandas as pd

str_list = [‘arun’, ‘courseone’, ‘python’, ‘skills’]

daf = pd.DataFrame(str_list)

print(daf)

Then after running this code in a Python editor or compiler, you will observe the following output. This is an example that shows you how you can convert the list into a data frame.

Output:

  • arun
  • courseone
  • python
  • skills

You can use the same method even when you are given a list of strings as the input. Let us see an example of that. Consider the following example:

Example-2:

import pandas as pd

# this is the list of strings

lst = [‘arun’, ‘is’, ‘content’, ‘writer’,

            ‘at’, ‘courseone’]

# here you will call a DataFrame constructor on the list

df = pd.DataFrame(lst)

df

Now, let us run and see the output for the above code:

Output:

  • arun
  • is
  • content
  • writer
  • at
  • courseone

Method-2:

When you are given lists of lists as an input. You can use this method to create a data frame object from the lists of lists.

I will show you an example so that you will understand this method much more clearly. So, consider the following example of this method:

Example-1:

# Consider this as an example for a List of lists

students = [ [‘arun’, 34, ‘India’] ,

             [‘Bharath’, 30, ‘canada’ ] ,

             [‘Swaru’, 16, ‘Korea’] ]

You need to pass this list to DataFrame’s constructor to create a data frame object

import pandas as pd

dfObj = pd.DataFrame(students)

print(dfObj)

The following is the output that shows the contents of the created dataframe:

      0   1         2

0  arun  34    India

1  Bharath  30     canada

2  Swaru  16  Korea

Method-3:

In this method, you will use a Zip() function to convert a list into data frames. You can use the same code file for further implementation and try to write the data frame by creating the code via Zip() function. Here, you need to import panda’s module and then create a list of strings and add items to it. You will create two lists in this method. One list is the list of strings and the other one is a list of integers. Then you need to call the dataframe constructor that will pass our list.

Now, you can assign the data frame constructor to a variable. Then you have to call the dataframe function. In this function, you will pass two parameters where the initial parameter is zip(), and the other one is the column. The zip() function helps you take iterable variables where you can combine them into a tuple. You can also use tuples, sets, lists, or dictionaries in this type of function in Python. You will observe that both files are zipped by the program with specified columns and then calls the data frame function.

Let us see an example of this:

Example-1:

import pandas as pd

string_list = [‘arun’, ‘courseone’, ‘coding, ‘skills’]

integer_list = [08,59,96,100]

df = pd.DataFrame(list(zip( string_list, integer_list)), columns = [‘key’, ‘value’])

print(df)

Now, when you run the above program, you will observe the following output.

Output:

      key  value

0     arun    08

1   courseone    59

2  coding     96

3  skills     100

Method-4:

This method is similar to the list of lists method. But, here, you will pass a list of tuples into the dataframe constructor to create a dataframe. You can use this method to create a data frame object from the lists of tuples given as input.

I will show you an example so that you will understand this method much more clearly. So, consider the following example of this method:

Example-1:

# consider the following as the List of Tuples

students = [ (‘arun’, 34, ‘india’) ,

             (‘bharath’, 30, ‘canada’ ) ,

             (‘swaru’, 16, ‘korea’) ]

To create a DataFrame object from the list dataframe’s constructor, all you have to do is to pass this list of tuples to DataFrame’s constructor.

import pandas as pd

# You need to create a DataFrame object from the list of tuple

dfObj = pd.DataFrame(students)

# This will display the DataFrame

print(dfObj)

The following is the output that shows the contents of the created dataframe:

      0   1         2

0  arun  34    india

1  bharath  30     canada

2  swaru  16  korea

Method-5:

In this method, a dictionary is used to convert a list into data frames. However, you will use the same “dataframe.py” code file to create data frames using lists in the dict. Here, you need to import the panda’s module first, and next your duty is to create a list of strings and add items to it. Your task is to create three lists in this method. They are the list of countries, programming languages, and integers. Now, it’s time to create a dict of lists and then you will have to assign it to a variable.

Consider the following example:

Example-1:

import pandas as pd

countryname = [“india”, “Us”, “Canada”, “korea”]

lang = [“C”, “Python”, “C++”, “java”]

var_list = [ 1, 4, 3, 5]

dict = { ‘countries’ : countryname, ‘Language’ : lang, ‘numbers’ : var_list

daf = pd.DataFrame(dict)

print(daf)

Hence, I conclude that these are the ways of converting a list to dataframe pandas in the Python programming language. However, these methods are a little confusing you can easily convert a given list to dataframe pandas using the above methods. So, I hope you will learn them.

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