React vs. Svelte: The War Between Virtual and Real DOM A quick look at the approaches taken by Svelte and React to build

React vs. Svelte: The War Between Virtual and Real DOM A quick look at the approaches taken by Svelte and React to build user interfaces and how they perform against each…blog.bitsrc.io

For a more comprehensive list of skills that you should learn, if you are studying to be a data scientist, I wrote a series of articles giving a complete roadmap for learning. They are linked below.

Data Analysis, A Complete Roadmap for Learning Data Science — Part 2 Part two of my complete roadmap for learning data science takes a look at the important skills needed for data…medium.com

Data science code is traditionally messy, not always well tested and lacking in adherence to styling conventions. This is fine for initial data exploration and quick analysis but when it comes to putting machine learning models into production then a data scientist will need to have a good understanding of software engineering principles.

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one quarantine in their bedroom when they’ve just flown on Thanksgiving weekend? This is the question my roommate Johnny and I found ourselves debating two weeks ago as our other roommate, Claire, planned her return to Boston after months spent with family in the Midwest. The three of us have shared an apartment in Boston’s leafy, lefty Jamaica Plain neighborhood for more than a year. Until now, our most arduous household challenges have been fixing the projector screen we use to watch movies or finding the source of a sudden sour stench in the fridge (spoiler: a bag of moldy cabbage from the farm where Johnny works). Claire’s return amid the fall Covid-19 surge changed everything.

There are several ways that you can install XlsxWriter. The easiest method would be using the Python package installer called pip. Open up a terminal and run the command pip install xlsxwriter.

Being able to extract data from a database and output it to Excel is a crucial skill to have as a Data Analyst. Today we are going to look at using a Python package called XlsxWriter to output a small DataFrame to Excel. XlsxWriter is a powerful package that you can use to auto-format Excel worksheets, change the styling and insert objects such as tables.

Save the above snippet to your local machine as xlsxwriter_hello_world.py. To execute the script, navigate to the directory where the file is saved and run the command python xlsxwriter_hello_world.py. The script will generate a file called testing_xlsxwriter.xlsx with ‘Hello World’ located in cell A1.

This is not meant as an exhaustive list, there are certainly a lot more skills and experience needed to become a successful data scientist. However, in this post, I wanted to cover some of the most important skills that are very likely to be required in the coming year.

You can use XlsxWriter as an engine for Pandas ExcelWriter class to output a DataFrame to Excel. Below we have included a simple script which will create a Pandas DataFrame with three columns and output it to an Excel file.

Programming Skills, A Complete Roadmap for Learning Data Science — Part 1 A complete guide to programming skills for data science, includes links to free learning resources.medium.com

I am noticing Airflow being mentioned more and more often as a desirable skill for data scientists on job adverts. As mentioned at the beginning of this article I believe it will become more important for data scientists to be able to build and manage their own data pipelines for analytics and machine learning. The growing popularity of Airflow is likely to continue at least in the short term, and as an open source tool, is definitely something that every budding data scientist should at learn.

If you are planning to work as a data scientist it is likely that you will either be putting models into production yourself or at least be involved heavily in the process. It is therefore essential to cover the following skills in any learning that you undertake.

Apache Airflow, an open source workflow management tool, is rapidly being adopted by many businesses for the management of ETL processes and machine learning pipelines. Many large tech companies such as Google and Slack are using it and Google even built their cloud composer tool on top of this project.

In this article, I wanted to highlight some of the key trends emerging in terms of the skills required for data scientists. These insights have been gleaned from reviewing current data science job adverts, my own experience working as a data scientist and reading articles covering future trends in the field.