So, you want to know what the Pandas library is in Python? Well, you came to the right place, because today we are going to break down exactly what Pandas is so you can be familiar with what this Python data science package is and how to get started with it! So without further ado, let’s jump right in.
What is Pandas In Python?
Pandas is an open-source Python library that is used within the data science and data analysis industry. The library gives you access to an amazing set of tools that makes working with data both much easier and faster.
In fact, if you are going to be working with data in Python, you are going to need to learn Pandas! It is used heavily in the data analysis, data science, and machine learning industries. Pandas is a must-learn if you want to work in any industry that utilizes Python and data.
Luckily for you, Pandas is a pretty intuitive library to work with and once you get the hang of it, you’ll fall in love with the process. Not to mention, it’s also free!
How To Install Pandas In Python?
Installing Pandas is really easy with the PIP Package Manager! All you need to do is run the command
pip install pandasWhat Can I Do With Pandas?
Pandas allows you to load, prepare, manipulate, model, and analyze data. Pandas is very simple to use and is very practical even for basic data analysis and manipulation. I actually recently made the switch to stop using excel and start using Pandas instead and I love it!
In Pandas, it’s really easy to create tables and manipulate the data. Here is an example of a table I created in Python with the Pandas library.
# 1. inside test.py file
import pandas as pd
df = pd.DataFrame({"Column Header 1" : ["Test1","Test2","Test3","Test4","Test5"],
"Column Header 2" : [25,30,35,40,45]})
print(df);
# 2. execute program from command line
>> python test.py
# 3. output from your console
>> python test.py
Column Header 1 Column Header 2
0 Test1 25
1 Test2 30
2 Test3 35
3 Test4 40
4 Test5 45What if we wanted to manipulate the table? Maybe get the mean of all the numbers in the second column? Well, we can very easily do that with the library too!
# 1. inside test.py file
import pandas as pd
df = pd.DataFrame({"Column Header 1" : ["Test1","Test2","Test3","Test4","Test5"],
"Column Header 2" : [25,30,35,40,45]})
meanOfColumn2 = df["Column Header 2"].mean()
print(meanOfColumn2)
# 2. execute program from command line
>> python test.py
# 3. output from your console
35.0If Pandas is still confusing to you or you don’t understand the code above, that’s okay! What’s important to know is that you can basically do any you want with data using Pandas. If you are a wiz with excel, know you can do anything in Pandas that you could do in excel and more.
It just means you need to learn Python and or learn Pandas. The limits of what you can do with Pandas are really the limits of your own knowledge of data manipulation, Python, and the Pandas library.
Where Can I Learn Pandas?
There are a ton of great resources online to learn about Pandas. If you are still a newbie at Python, I suggest checking out my article on getting started with Python, here.
If you feel pretty comfortable with Python and want to jump right into Pandas, you can check out this really great tutorial by Boris Paskhaver that will make you a pro in no time!
Summary
Pandas is a free Python library that is used heavily in the data science, data manipulation, and machine learning industries. If you’re looking into one of those fields, it will benefit you a lot to learn Pandas!
Pandas allows you to create, display, manipulate, model, and analyze data easily and quickly. It is an incredibly useful tool that any programmer should know.
Happy coding!
