In this article, we will understand what lists and data frames are. We will also study different ways to convert the list to the data frame in python programming. This also answers how to create a pandas data frame from the list in python. So, let’s get started!
What is a List?
The list is the most important data type in python programming. In Python, the list is written as the list of commas separated values inside the square bracket. The most important advantage of the list is the elements inside the list are not compulsorily be of the same data type along with negative indexing. Also, all the operation of the string is similarly applied on list data type such as slicing, concatenation, etc. Also, we can create a nested list i.e. list containing another list.
For Example
# creating a list of items with different data types sample_list = [10,"favtutor",['A','B']] print(sample_list)
Output
[10, 'favtutor', ['A', 'B']]
What is a Data Frame?
Pandas is a software library written for the Python programming language for data manipulation and analysis. Pandas Dataframe is a two-dimensional size-mutable, potentially heterogeneous tabular data structure with labeled axes (rows and columns). A data frame could be a two-dimensional data structure, i.e., knowledge is aligned in a very tabular fashion in rows and columns. Pandas Dataframe consists of 3 principal elements, the data, rows, and columns.
For Example
import pandas as pd # list of strings lst = ['fav', 'tutor', 'coding', 'skills'] df = pd.DataFrame(lst) print(df)
Output
0 0 fav 1 tutor 2 coding 3 skills
Convert List to DataFrame in Python
There are many ways to create a data frame from the list. We will look at different 6 methods to convert lists from data frames in Python. Let us study them one by one with an example:
1) Basic method
This is the simplest method to create the data frames from the list.
For example
# import pandas as pd import pandas as pd # list of strings lst = ['fav', 'tutor', 'coding', 'skills'] # Calling DataFrame constructor on list df = pd.DataFrame(lst) print(df)
Output
0 0 fav 1 tutor 2 coding 3 skills
2) Using a list with index and column names
We can create the data frame by giving the name to the column and index the rows
For example
# import pandas as pd import pandas as pd # List1 lst = [['apple', 'red', 11], ['grape', 'green', 22], ['orange', 'orange', 33], ['mango', 'yellow', 44]] df = pd.DataFrame(lst, columns =['Fruits', 'Color', 'Value'], dtype = float) print(df)
Output
tutorial 1 fav 2 tutor 3 coding 4 skills
3) Using zip() function
We can create the data frame by zipping two lists.
For example
# import pandas as pd import pandas as pd # list of strings lst1 = ['fav', 'tutor', 'coding', 'skills'] # list of int lst2 = [11, 22, 33, 44] # Calling DataFrame after zipping both lists, with columns specified df = pd.DataFrame(list(zip(lst1, lst2)), columns =['key', 'value']) print(df)
Output
key value 0 fav 11 1 tutor 22 2 coding 33 3 skills 44
4) Creating from the multi-dimensional list
We can create a data frame using multi-dimensional lists.
For example
# import pandas as pd import pandas as pd # List1 lst = [['fav', 11], ['tutor', 22], ['coding', 33], ['skills', 44]] df = pd.DataFrame(lst, columns =['key', 'values']) print(df)
Output
key values 0 fav 11 1 tutor 22 2 coding 33 3 skills 44
5) Using a multi-dimensional list with column name
We can create the data frames by specifying the column name and dtype of them.
For example
# import pandas as pd import pandas as pd # List1 lst = [['apple', 'red', 11], ['grape', 'green', 22], ['orange', 'orange', 33], ['mango', 'yellow', 44]] df = pd.DataFrame(lst, columns =['Fruits', 'Color', 'Value'], dtype = float) print(df)
Output
Fruits Color Value 0 apple red 11.0 1 grape green 22.0 2 orange orange 33.0 3 mango yellow 44.0
6) Using a list in the dictionary
We can create data frames using lists in the dictionary.
For example
# import pandas as pd import pandas as pd # list of name, degree, score n = ["apple", "grape", "orange", "mango"] col = ["red", "green", "orange", "yellow"] val = [11, 22, 33, 44] # dictionary of lists dict = {'fruit': n, 'color': col, 'value': val} df = pd.DataFrame(dict) print(df)
Output
fruit color value 0 apple red 11 1 grape green 22 2 orange orange 33 3 mango yellow 44
Conclusion
While working with a large set of data, it is important to convert the data into a format for easy understanding and operations. Panda data frame provides such an easy format to access the data effectively and efficiently. As we all know that data in python is mostly provided in the form of a List and it is important to convert this list into a data frame.
If you want to practice pandas skills then you can check out Pandas exercises for Beginners.
