Hire Pandas developers

As Pandas is a library for Python, a Pandas developer’s salary will be more or less within the higher end of the Python developer’s salary range, which is $119k – $145k per year (according to Glassdoor). You are free to check out the Python developers with extensive experience with Pandas on the Lemon.io platform: here you’ll pay only for the hours worked at a rate the programmer is comfortable with, making the cooperation process transparent and aligned for each party.

Such companies as Netflix, Microsoft, Google, and Facebook all use Pandas! These tech giants, as well as thousands of others, all have one thing in common — huge amounts of data that need to be analyzed in order for the companies to drive their initiatives forward. Pandas is a great choice for data science and analysis, and it has earned itself huge popularity in fintech, e-commerce, healthcare, and other domains.

You can hire a Pandas developer through Lemon.io in just a couple of days! It usually takes us from 24 to 48 hours to find candidates who check all the boxes from your requirements list. Then, as long as you like the candidates you see and your company’s internal selection process is speedy, it might take only another day or two to choose the perfect contractor for your endeavor!

Yes, Pandas is still in demand and is also one of the most popular data science tools on the market today! More and more companies are incorporating data science and machine learning to keep up with the latest trends in the world and drive their initiatives forward. As Pandas remains a powerful but, at the same time, very user-friendly tool to help with data manipulation and analysis for those particular tasks, it’s no wonder why the Pandas community is thriving at the moment.

A no-risk trial period for hiring a Pandas developer on Lemon.io is a paid trial (up to 20 hours) in case you want to double-check that the chosen developer does well with real-world tasks and gets on well with the rest of the team before signing up for a subscription.
Also, in case your Lemon.io developer misses deadlines or fails to meet expectations, we’ll match you with a new remote developer asap. Admittedly, we’ve never had to do this. But it’s our promise. Just in case.

To hire a Pandas developer through Lemon.io, you need to make a request: tell us a bit about your project and the most important requirements for potential candidates. After that, we will get back to you with a couple of hand-picked, pre-vetted developers who check all the boxes. You can be confident in the candidates’ soft skills and technical expertise, as they are checked by our team, but you are also welcome to have a few calls with the devs, just to make sure. Pick the right talent and get started today!

No, Pandas does not actually replace SQL. It has some same or similar functionalities, though. Developers use SQL if they deal with the management of relational databases. On the other hand, major uses of Pandas include Data Analysis and Manipulation.

If you have large amounts of data, then use SQL, as Pandas might be a tad too slow. Sometimes the best option is to use both tools for exactly what they do best: SQL to manage the database and query your data, then Pandas for data analysis or manipulation.

Yes, Pandas is open-source and free to use, which is why so many companies choose it for their endeavors. Just imagine: you have one of the best tech tools to work with data analysis and manipulation; it has a large and supportive community, is fairly easy to get started with, and even has a very lenient license for commercial use. What is there not to like?

No, unfortunately, Pandas is not very good for big data. There are a few reasons for that, but the main point is that Pandas simply cannot load a dataset that is bigger than your machine’s memory. Pandas is still really good with small or mid-sized data, though. If you are looking for something similar that would actually work well with big data, then PySpark is the way to go (btw, come check both Pandas and PySpark developers on Lemon.io).

Pandas is a library. It isn’t restrictive enough to be called a framework: it doesn’t dictate what architecture you have to build, doesn’t control your application and its structure, and works only when you tell it to. Because of its flexibility, it is considered a library.