2018 New Year resolution — Learn Pandas, Day 1

During the Christmas break last year I took the Coursera MOOC: Introduction to Data Science in Python. It gave me a quick start in using Pandas (Python Data Analysis Library) and I directly started to use it for the data wrangling I do in my daily work on clinical trial metadata: Pandas and Jupyter to cope with one clinical study — many names/codes. I have created 25+ Jupyter notebooks during 2017 to bring together and analyse metadata about clinical trials, clinical trial documents and clinical trial datasets. I really like it.

However, I also feel that my knowledge is too shallow and when I saw a blog post by Ted Petrou on How to Learn Pandas it made me think.

So, one of my New Year resolutions for 2018 is to learn Pandas in more depth. I will post a couple of blog posts with pointers to the resources I am using and key insights I hope to get.

Day 1

Listening to the Podcast: Pandas — The Swiss Army Knife of Data with Jeff Reback (@jereback) from Podcast__init__ Gave me a good overview, history and key benefits of using Pandas.

Listening to the podcast triggered me to donate a small amount of money to support this great open source project.

Following the advice by Ted Petrou I digged into the core chapter in the Pandas documentation on Data Structures by creating a notebook and writing (not copying) the code. It gave me a better understanding of Series and DataFrames.

The last thing I did this first day of 2018, and of my learning Pandas exercise, was to download the Pandas Cheat Sheet on Data Wrangling.

Like what you read? Give Kerstin Forsberg a round of applause.

From a quick cheer to a standing ovation, clap to show how much you enjoyed this story.