Working with messy data sets is a common challenge.

2mo ago

10 replies

What are your favorite tools or techniques for cleaning and transforming data to make it analysis-ready?

Replies

Cleaning messy data is like untangling headphone wires - time-consuming but necessary! I rely on the dynamic duo of Python libraries like Pandas and Numpy to whip data into shape for smooth analysis. How do you tackle your data cleaning dilemmas?

Jul 24

Yatheen Brahma @yatheen_brahma

Launching soon!

I used to do it on excel.

Jul 23

Arthur Leo @ar_th_ur_leo

I often use Python with pandas. It’s great for handling large datasets and has many useful functions for cleaning data.

Jul 23

Dipmala Kumari @dipmala_kumari

Did you use OpenRefine? It's perfect for cleaning messy data and transforming it.

Jul 23

Umaru @umaru_sanda

I use R with the dplyr package. It’s great for data manipulation and cleaning tasks.

Jul 23

Ishaku Abdullahi @ishaku_abdullahi

I use Python tools like Pandas for cleaning data. They make it easy to fix problems and get the data ready for analysis.

Jul 24

Ibrahim yasir Suleiman @ibrahim_yasir_suleiman

OpenRefine is really helpful for cleaning data. It can remove duplicates and fix errors

Jul 24

Ibrahim adamu @ibrahim_adamu_bt

I use SQL to clean data. It helps me filter and organize data quickly.

Jul 24

Ado Audu @ado_audu

Alteryx is a good tool for cleaning data. It has an easy-to-use interface for preparing data.

Jul 24

Hassan Fiaz @hassan_fiaz

I use R with packages like dplyr for cleaning data. It helps me transform data into the right format for analysis.

Jul 24