Jason Malefakiswayo.hashnode.dev·Nov 15, 2024Why Pandas is Essential to Efficient Data EngineeringPython is the quintessential data analytics language with its simplicity, versatility, and huge library ecosystem. Though Python on its own seriously tackles many data tasks, the Pandas library (a portmanteau of panel data - multi-dimensional data se...Discusspandas
Steve Hatmaker Jr.forSteve Hatmaker Jrstevehatmakerjr.com·Nov 12, 2024Finding eBay Items with Python and Exporting to ExcelWhy Build an eBay Search Tool? If you collect items like entertainment memorabilia or retro gaming consoles, you know that finding specific listings can be time-consuming. This Python program automates that search by connecting to the eBay API, retri...Discussebay search
Rohit Kumarcustomer-demographic-analysis.hashnode.dev·Nov 5, 2024Exploring Customer Demographics with Data Analysis: Insights from Istanbul's Shopping MallsIntroduction This project is a deep dive into customer demographic analysis, exploring shopping trends across 10 malls in Istanbul from 2021 to 2023. Through this dataset, I aimed to uncover insights about customer behavior, from spending habits acro...Discuss·1 likedata analysis
Ashmit Kantiashmitandcoding.hashnode.dev·Oct 24, 2024All about Pandas and NumpyNumpy NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. Guide to Numpy: - NumPy user...Discusspandas
Sachin PalforTeam - GeekPythonteamgeek.geekpython.in·Oct 23, 2024Pandas df.ffill() and df.bfill()The DataFrame.ffill() (forward fill) propagates missing or NaN values using the previous valid value in a column or row, while DataFrame.bfill() (backward fill) propagates them using the next valid value. Let's see how and when to use them. DataFrame...Discusspandas
Roemairoemai.hashnode.dev·Oct 21, 2024Real-Life House Price Prediction with Linear RegressionPredicting house prices is a key part of real estate analytics, and in this project, I’ll walk you through how I built a machine learning model using linear regression to predict house prices. Project Overview We start with a dataset that contains in...DiscussArtificial Intelligence
Sai Sravanthisaisravanthi.hashnode.dev·Oct 21, 2024Data Cleaning Best PracticesIn the world of data analysis, data cleaning is a crucial but often overlooked step. The quality of your analysis is only as good as the data you're working with. Even the most sophisticated algorithms and models will fail if the underlying data is m...Discussdata cleaning
Sai Sravanthisaisravanthi.hashnode.dev·Oct 12, 2024Using Python for Data Analysis: Libraries and Best PracticesPython has become the go-to language for data analysis due to its simplicity, versatility, and powerful libraries. With an active community and extensive documentation, it enables both beginners and experienced analysts to manipulate, analyze, and vi...DiscussPython
Sachin PalforTeam - GeekPythonteamgeek.geekpython.in·Oct 10, 2024Enabling Copy on Write in Pandas for Efficient Memory ManagementPandas supports Copy-on-Write, an optimization technique that helps improve memory use, particularly when working with large datasets. Starting from version 2.0 of Pandas, the Copy-on-Write (CoW) has taken effect but has not been fully implemented. M...Discusspandas
Akshobya KLakshobya.hashnode.dev·Oct 9, 2024Exploring Pandas: Our Go-To Library for Data ManipulationWhen it comes to data engineering in Python, Pandas is often our first stop. This powerful library provides an intuitive way to handle and manipulate data, making it a staple for data engineers, analysts, and scientists alike. Let’s dive into what ma...Discusspandas
