HellO!?
Today I'm back with a new notebook which demonstrates a way of working with data in Jupyter.
Source file
I downloaded the dataset from
Kaggle a platform to find real-world data and connect with other data enthusiasts.
There you will find an incredible collection of datasets and projects and you can also participate in competitions.
Short evidence of the work
After I returned a concise summary of the dataframe I performed the cleaning of data, to get my data into a usable and consistent format for analysis
astype() method is used to convert a pandas object to a specified data type.
I used fillna(0) to get rid of the error that initially appeared. Try it yourself!
Where is the rest of the work? ?
You can find more in my GitHub repository. Here I uploaded the notebook and of course the dataset. In short words, you will learn how to
load a dataframe,
examine its metadata,
convert data types
explore the dataframe using iloc indexing.
More than that, you will learn about Boolean masking and...how to calculate the median value. ?
Are you ready to explore the data?
The above is the detailed content of Working with DataFrames in Pandas. For more information, please follow other related articles on the PHP Chinese website!
How to Use Python to Find the Zipf Distribution of a Text FileMar 05, 2025 am 09:58 AMThis tutorial demonstrates how to use Python to process the statistical concept of Zipf's law and demonstrates the efficiency of Python's reading and sorting large text files when processing the law. You may be wondering what the term Zipf distribution means. To understand this term, we first need to define Zipf's law. Don't worry, I'll try to simplify the instructions. Zipf's Law Zipf's law simply means: in a large natural language corpus, the most frequently occurring words appear about twice as frequently as the second frequent words, three times as the third frequent words, four times as the fourth frequent words, and so on. Let's look at an example. If you look at the Brown corpus in American English, you will notice that the most frequent word is "th
How Do I Use Beautiful Soup to Parse HTML?Mar 10, 2025 pm 06:54 PMThis article explains how to use Beautiful Soup, a Python library, to parse HTML. It details common methods like find(), find_all(), select(), and get_text() for data extraction, handling of diverse HTML structures and errors, and alternatives (Sel
Image Filtering in PythonMar 03, 2025 am 09:44 AMDealing with noisy images is a common problem, especially with mobile phone or low-resolution camera photos. This tutorial explores image filtering techniques in Python using OpenCV to tackle this issue. Image Filtering: A Powerful Tool Image filter
How to Work With PDF Documents Using PythonMar 02, 2025 am 09:54 AMPDF files are popular for their cross-platform compatibility, with content and layout consistent across operating systems, reading devices and software. However, unlike Python processing plain text files, PDF files are binary files with more complex structures and contain elements such as fonts, colors, and images. Fortunately, it is not difficult to process PDF files with Python's external modules. This article will use the PyPDF2 module to demonstrate how to open a PDF file, print a page, and extract text. For the creation and editing of PDF files, please refer to another tutorial from me. Preparation The core lies in using external module PyPDF2. First, install it using pip: pip is P
How to Cache Using Redis in Django ApplicationsMar 02, 2025 am 10:10 AMThis tutorial demonstrates how to leverage Redis caching to boost the performance of Python applications, specifically within a Django framework. We'll cover Redis installation, Django configuration, and performance comparisons to highlight the bene
How to Perform Deep Learning with TensorFlow or PyTorch?Mar 10, 2025 pm 06:52 PMThis article compares TensorFlow and PyTorch for deep learning. It details the steps involved: data preparation, model building, training, evaluation, and deployment. Key differences between the frameworks, particularly regarding computational grap
Introduction to Parallel and Concurrent Programming in PythonMar 03, 2025 am 10:32 AMPython, a favorite for data science and processing, offers a rich ecosystem for high-performance computing. However, parallel programming in Python presents unique challenges. This tutorial explores these challenges, focusing on the Global Interprete
How to Implement Your Own Data Structure in PythonMar 03, 2025 am 09:28 AMThis tutorial demonstrates creating a custom pipeline data structure in Python 3, leveraging classes and operator overloading for enhanced functionality. The pipeline's flexibility lies in its ability to apply a series of functions to a data set, ge
Hot AI Tools
Undresser.AI Undress
AI-powered app for creating realistic nude photos
AI Clothes Remover
Online AI tool for removing clothes from photos.
Undress AI Tool
Undress images for free
Clothoff.io
AI clothes remover
AI Hentai Generator
Generate AI Hentai for free.
Hot Article
Hot Tools
SublimeText3 Mac version
God-level code editing software (SublimeText3)
mPDF
mPDF is a PHP library that can generate PDF files from UTF-8 encoded HTML. The original author, Ian Back, wrote mPDF to output PDF files "on the fly" from his website and handle different languages. It is slower than original scripts like HTML2FPDF and produces larger files when using Unicode fonts, but supports CSS styles etc. and has a lot of enhancements. Supports almost all languages, including RTL (Arabic and Hebrew) and CJK (Chinese, Japanese and Korean). Supports nested block-level elements (such as P, DIV),
SublimeText3 Chinese version
Chinese version, very easy to use
EditPlus Chinese cracked version
Small size, syntax highlighting, does not support code prompt function
VSCode Windows 64-bit Download
A free and powerful IDE editor launched by Microsoft
