{"id":8762,"date":"2022-05-08T12:43:00","date_gmt":"2022-05-08T16:43:00","guid":{"rendered":"https:\/\/stringfestanalytics.com\/?p=8762"},"modified":"2023-01-28T09:35:41","modified_gmt":"2023-01-28T14:35:41","slug":"free-checklist-30-days-to-python-programmer","status":"publish","type":"post","link":"https:\/\/stringfestanalytics.com\/free-checklist-30-days-to-python-programmer\/","title":{"rendered":"Free checklist: 30 days to Python programmer"},"content":{"rendered":"

Python has become in many ways the lingua franca <\/em>of computing<\/a>, with the open source language<\/a> being used in everything from web development to artificial intelligence to… why, yes… data analytics. <\/p>\n

If you’re a heavy Excel or Power BI user, Python is a great tool to add to your toolkit — it’s officially supported in Power BI<\/a> now and an official integration with Excel is coming (although there are already cool ways to use Python with Excel<\/a>.).<\/p>\n

The interoperability is to the point where it’s about learning Python instead <\/em>of Power BI, Excel, etc. They are meant to be used together.<\/em><\/p>\n

\n
\"\"<\/figure>\n<\/div>\n

Moreover, data analysts already know a fair amount about computing. It’s a lot easier to learn Python with this skillset than for the average person off the street. With that lessened learning curve, it’s easy to reap big rewards as an analyst with relatively modest Python skills. In fact, Burning Glass found that jobs requiring coding skills pay $22,000 per year more<\/a> than those that don’t. <\/p>\n

You may not get that kind of bump from this checklist… but it’s a start! <\/p>\n

Get the free checklist below \ud83d\udc47<\/h2>\n

Be sure to subscribe for complete access to my analytics resource library<\/h4>\n