Anix Lynchgozeroshot.dev·Dec 6, 202430 Frequently used Dataprep library functions w/samplesHere are examples using the dataprep library for data preparation tasks: 1. Loading and Cleaning Data from dataprep.datasets import load_dataset from dataprep.clean import clean_headers # Load dataset df = load_dataset("titanic") # Clean column he...Python
Muhammad Zafarzafarr.hashnode.dev·Nov 29, 2024Practical Guide to Handle Missing Values in DatasetsEver opened a dataset only to find it's full of holes like Swiss cheese? Don't worry - missing values are a common challenge in data science, and today we'll learn how to handle them effectively. Understanding Missing Values Missing values are gaps i...dealing with missing values
Anastasia Zaharievawhenmathmetdata.hashnode.dev·Nov 26, 2024Day 9: Cleaning Data (Handling Missing Data and Outliers)Welcome to Day 9! Today, we’re focusing on one of the most crucial steps in the data analysis process: cleaning data. This step ensures that the data is accurate, consistent, and ready for analysis. We will cover techniques for handling missing data ...30 Days Data Science ChallengePython
pallavi chauhaninnovateitworld.hashnode.dev·Nov 12, 2024Data Science Career Paths: Which Role is Right for You?As the field of data science continues to evolve, organizations across industries are leveraging data to inform their decisions and drive growth. The surge in big data and machine learning has led to a growing demand for data science professionals, r...Data Science
Shivanshi Singhshivanshi770.hashnode.dev·Oct 21, 2024Why is Data Quality Important in Machine Learning?Introduction Machine learning models are only as good as the data that powers them. High-quality data ensures the reliability, accuracy, and relevance of model outcomes, making it a critical aspect of any machine learning project. This article explor...Data Science
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...data cleaning
Sandhya Kondmarekloudsan.hashnode.dev·Oct 6, 2024Feature Engineering: A Key Step in Machine Learning"feature" ka matlab dataset mein woh columns hote hain jo specific information ko represent karte hain. Yani, feature kisi bhi characteristic ya attribute ko define karta hai jo aapke analysis ke liye important hai. Example ke liye: Agar aap ek datas...DataPreprocessing
Shivanshi Singhshivanshi770.hashnode.dev·Sep 30, 2024Getting Started with NumPy for Data ScienceNumPy (Numerical Python) is a powerful library for numerical computing in Python, widely used in data science for its efficiency in handling large datasets and mathematical operations. In this article, we’ll explore the basics of NumPy, its importanc...numpy
Shivanshi Singhshivanshi770.hashnode.dev·Sep 26, 2024How to Read and Interpret Data: A Beginner’s GuideIn today’s data-driven world, the ability to read and interpret data is a crucial skill. Whether you're a beginner in data analysis or just starting to incorporate data into your decision-making process, understanding how to work with data is essenti...Data Science
Ogunmesi Tobilobaogunmesitobiloba.hashnode.dev·Sep 24, 2024Analyzing Customer Retention: Dashboard Insights and Data-Driven RecommendationsIn today's competitive market, understanding customer retention is paramount for business success. The dashboards presented provide a detailed view of key factors impacting customer retention, ranging from service charges to churn rates. This analysi...data analysis
