# 10 Amazing Applications of Pandas – Which Industry Segment is Using Python Pandas?

It is essential to have a solid idea about how exactly one should apply one’s knowledge because knowledge obtain very easily, but to use it accurately is what makes you wise. Therefore, in this 10 Amazing Applications of Pandas, we have shortlisted the mind-blowing applications and various places where you can apply the knowledge of Pandas in the real world.

With the help of this list, you will know which sectors of the industry apply Python pandas in real-world.

## Major Applications of Pandas

In this list we will cover the most fundamental applications of Pandas:

### 1. Economics

Economics is in constant demand for data analysis. Analyzing data to form patterns and understanding trends about how the economy in various sectors is growing, is something very essential for economists. Therefore, a lot of economists have started using Python and Pandas to analyze huge datasets. Pandas provide a comprehensive set of tools, like dataframes and file-handling. These tools help immensely in accessing and manipulating data to get the desired results. Through these applications of Pandas, economists all around the world have been able to make breakthroughs like never before.

### 2. Recommendation Systems

We all have used Spotify or Netflix and been appalled at the brilliant recommendations provided by these sites. These systems are a **miracle of Deep Learning**. Such models for providing recommendations is one of the most important applications of Pandas. Mostly, these models are made in python and Pandas being the main libraries of python, used when handling data in such models. We know that Pandas are best for managing huge amounts of data. And the recommendation system is possible only by learning and handling huge masses of data. Functions like groupBy and mapping help tremendously in making these systems possible.

### 3. Stock Prediction

The stock market is extremely volatile. However, that doesn’t mean that it cannot be predicted. With the help of Pandas and a few other libraries like **NumPy** and matplotlib, we can easily make models which can predict how the stock markets turn out. This is possible because there is a lot of previous data of stocks which tells us about how they behave. And by learning these data of stocks, a model can easily predict the next move to be taken with some accuracy. Not only this, but people can also automate buying and selling of stocks with the help of such prediction models.

### 4. Neuroscience

Understanding the nervous system has always been in the minds of humankind because there are a lot of potential mysteries about our bodies which we haven’t solved as of yet. **Machine learning** has helped this field immensely with the help of the various applications of Pandas. Again, the data manipulation capabilities of Pandas have played a major role in compiling a huge amount of data which has helped neuroscientists in understanding trends that are followed inside our bodies and the effect of various things on our entire nervous system.

### 5. Statistics

Pure maths itself has made much progress with the various applications of Pandas. Since Statistic deals with a lot of data, a library like Pandas which deals with data handling has helped in a lot of different ways. The functions of mean, median and mode are just very basic ones which help in performing statistical calculations. There are a lot of other complex functions associated with statistics and pandas plays a huge role in these so as to bring perfect results.

### 6. Advertising

**Advertising** has taken a huge leap in the 21st Century. Nowadays advertising has become very personalized which helps companies to get more and more customers. This again has been possible only because of the likes of Machine Learning and Deep Learning. Models going through customer data learn to understand what exactly the customer wants, providing companies with great advertisement ideas. There are many applications of Pandas in this. The customer data often rendered with the help of this library, and a lot of functions present in Pandas also help.

### 7. Analytics

Analytics has become easier than ever with the use of Pandas. Whether it is website analytics or analytics of some other platform, Pandas do it all, with its amazing data manipulation and handling capabilities. The visualization capabilities of pandas play a big role too in this field. It not only takes in data and displays it but also helps in applying a lot of functions over the data.

### 8. Natural Language Processing

NLP or **Natural Language processing** has taken the world by a storm and it is creating a lot of buzzes. The main concept is to decipher human language and several nuances related to it. This is very difficult, but with the help of the various applications of Pandas and Scikit-learn, it is easier to create an NLP model which we can be improved continuously with the help of various other libraries and their functions.

### 9. Big Data

One of the applications of Pandas is that it can work with Big data too. Python has a good connection with Hadoop and Spark, allowing Pandas to have access to Big Data. One can easily write to Spark or **Hadoop** also with the help of Pandas.

### 10. Data Science

Pandas and Data science are almost synonymous. Most of the examples are a product of Data Science itself. It is a very broad umbrella which encompasses anything that deals with analyzing data, and thus almost all applications of Pandas fall under the **scope of Data science**. Pandas mainly used for processing the data. Therefore Data Science on Python without Pandas is very difficult.

## Summary

Through the above-given examples, we have come across a comprehensive list of various real-time applications of Pandas. These applications found in our day-to-day lives and are very helpful in the real world. Now, By knowing them, I hope you will easily be able to make out about where and how exactly you can apply your knowledge. You may also like to know **15 Advanced Features of Pandas**.

Please provide us feedback on the blog and help us improve.