Problem: You’re given a list of lists. Your goal is to convert it into a Pandas Dataframe.
Example: Say, you want to compare salary data of different companies and job descriptions. You’ve obtained the following salary data set as a list of list:
salary = [['Google', 'Machine Learning Engineer', 121000],
['Google', 'Data Scientist', 109000],
['Google', 'Tech Lead', 129000],
['Facebook', 'Data Scientist', 103000]]How can you convert this into a Pandas Dataframe?
DataFrame()
Solution: The straight-forward solution is to use the pandas.DataFrame() constructor that creates a new Dataframe object from different input types such as NumPy arrays or lists.
Here’s how to do it for the given example:
import pandas as pd
salary = [['Google', 'Machine Learning Engineer', 121000],
['Google', 'Data Scientist', 109000],
['Google', 'Tech Lead', 129000],
['Facebook', 'Data Scientist', 103000]]
df = pd.DataFrame(salary)This results in the following Dataframe:
print(df)
'''
0 1 2
0 Google Machine Learning Engineer 121000
1 Google Data Scientist 109000
2 Google Tech Lead 129000
3 Facebook Data Scientist 103000
'''Try It Yourself: Run this code in our interactive Python shell by clicking the “Run” button.
DataFrame.from_records()
An alternative is the pandas.DataFrame.from_records() method that generates the same output:
import pandas as pd
salary = [['Company', 'Job', 'Salary($)'],
['Google', 'Machine Learning Engineer', 121000],
['Google', 'Data Scientist', 109000],
['Google', 'Tech Lead', 129000],
['Facebook', 'Data Scientist', 103000]]
df = pd.DataFrame.from_records(salary)
print(df)
'''
0 1 2
0 Google Machine Learning Engineer 121000
1 Google Data Scientist 109000
2 Google Tech Lead 129000
3 Facebook Data Scientist 103000
'''
Try It Yourself: Run this code in our interactive Python shell by clicking the “Run” button.
Column Names
If you want to add column names to make the output prettier, you can also pass those as a separate argument:
import pandas as pd
salary = [['Google', 'Machine Learning Engineer', 121000],
['Google', 'Data Scientist', 109000],
['Google', 'Tech Lead', 129000],
['Facebook', 'Data Scientist', 103000]]
df = pd.DataFrame(salary, columns=['Company', 'Job', 'Salary($)'])
print(df)
'''
Company Job Salary($)
0 Google Machine Learning Engineer 121000
1 Google Data Scientist 109000
2 Google Tech Lead 129000
3 Facebook Data Scientist 103000
'''Try It Yourself: Run this code in our interactive Python shell by clicking the “Run” button.
If the first list of the list of lists contains the column name, use slicing to separate the first list from the other lists:
import pandas as pd
salary = [['Company', 'Job', 'Salary($)'],
['Google', 'Machine Learning Engineer', 121000],
['Google', 'Data Scientist', 109000],
['Google', 'Tech Lead', 129000],
['Facebook', 'Data Scientist', 103000]]
df = pd.DataFrame(salary[1:], columns=salary[0])
print(df)
'''
Company Job Salary($)
0 Google Machine Learning Engineer 121000
1 Google Data Scientist 109000
2 Google Tech Lead 129000
3 Facebook Data Scientist 103000
'''Slicing is a powerful Python feature and before you can master Pandas, you need to master slicing. To refresh your Python slicing skills, download my ebook “Coffee Break Python Slicing” for free.
Summary: To convert a list of lists into a Pandas DataFrame, use the pd.DataFrame() constructor and pass the list of lists as an argument. An optional columns argument can help you structure the output.
Programmer Humor
There are only 10 kinds of people in this world: those who know binary and those who don’t.
👩🧔♂️
~~~
There are 10 types of people in the world. Those who understand trinary, those who don’t, and those who mistake it for binary.
👩🧔♂️👱♀️
Where to Go From Here?
Enough theory. Let’s get some practice!
Coders get paid six figures and more because they can solve problems more effectively using machine intelligence and automation.
To become more successful in coding, solve more real problems for real people. That’s how you polish the skills you really need in practice. After all, what’s the use of learning theory that nobody ever needs?
You build high-value coding skills by working on practical coding projects!
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🚀 If your answer is YES!, consider becoming a Python freelance developer! It’s the best way of approaching the task of improving your Python skills—even if you are a complete beginner.
If you just want to learn about the freelancing opportunity, feel free to watch my free webinar “How to Build Your High-Income Skill Python” and learn how I grew my coding business online and how you can, too—from the comfort of your own home.