Why Is Python the Language of Choice for Data Scientists?
Python has grown to become one of the most popular and well-liked programming languages in the world, used by millions of developers since its creation in 1991. For data scientists in particular, Python has a strong, long-time base of developers. Why is Python the language of... Read more
PyCharm vs. VSCode: Which Is the Better Python IDE?
Python first debuted in 1991, making it older than many of the people who use it. In the intervening years, coders have turned it into one of the most popular programming languages ever conceived. The reasons for Python’s perennial popularity come down to three major features.... Read more
Supercharge Your Pandas Code with Apache Spark
Editor’s Note: Itai Yaffe and Daniel Haviv are speakers for ODSC East 2022. Be sure to check out their talk, “A bamboo of Pandas: crossing Pandas’ single-machine barrier with Apache Spark,” there! Pandas is a fast and powerful open-source data analysis and manipulation framework written in... Read more
3 Easy Tricks to Create New Columns in Python Pandas
In data processing & cleaning, we need to create new columns based on values in existing columns. In this blog, I explain How to create new columns derived from existing columns” with 3 simple methods. · Use lambda Function with apply() method · Use numpy.select() method... Read more
Data science teams are multidisciplinary, each with different skills and technologies of choice. Some of them use SAS, others may have analytical assets already built in Python or R. Let’s just say each team is unique. As part of our Continuous Integration/Continuous Delivery with monthly releases,... Read more
6 Trending Python Machine Learning Packages on PyPI
As the most popular programming language for data science, Python packages, frameworks, and libraries are pulled by the millions each month. Month-to-month, Python packages reflect growing trends in the field of data science; as NLP is talked about more often, so will we see more packages... Read more
Systems built with software can be fragile. While the software is highly predictable, the runtime context can provide unexpected inputs and situations. Devices fail, networks are unreliable, mere anarchy is loosed on our application. We need to have a way to work around the spectrum of... Read more
5 Reasons to Learn Python in 2021
You never hear about data science without hearing about Python as well, and for good reason as it’s the most common language for data scientists. In fact, 69% of data scientists report using Python, compared to 24% using R. This doesn’t mean Python is superior in... Read more
Develop and Deploy a Machine Learning Pipeline in 45 Minutes with Ploomber
It’s standard industry practice to prototype Machine Learning pipelines in Jupyter notebooks, refactor them into Python modules and then deploy using production tools such as Airflow or Kubernetes. However, this process slows down development as it requires significant changes to the code. Ploomber enables a leaner... Read more
Decoupling Complex Systems with Event Driven Python Programming
We often think about events as ordered points in time that happen one after another, often with some kind of cause-effect relationship. But, in programming, events are often understood a bit differently. They are not necessarily “things that happen.” Events in programming are more often understood... Read more