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Data preparation is a crucial step in data science that involves transforming raw data into a clean, usable format for analysis and modeling. Data preparation involves several steps, such as handling missing values, standardizing data formats, encoding categorical data and feature scaling. Why Data Preparation is Important Data in its raw form often contains inconsistencies, … Read more
In data science, Functions in Python allow data scientists to perform specific tasks repeatedly, such as data cleaning, transformation or statistical calculations, without rewriting code. What is a Function? A function is a reusable block of code that performs a specific task. Functions can take inputs, process them, and return outputs. They help organize code … Read more
What is a DataFrame? A DataFrame is a table-like structure with rows and columns, similar to an Excel spreadsheet or SQL table. Each column in a DataFrame can hold data of different types (e.g., integers, floats, strings), and each row represents an individual observation or record. This flexibility and easy accessibility make DataFrames the most … Read more
Python is one of the most popular programming languages in data science due to its simplicity, versatility and robust ecosystem of libraries tailored for data analysis, machine learning and statistical operations. Learning Python is often the first step for aspiring data scientists because it enables them to efficiently handle, manipulate and analyze data, ultimately providing … Read more
Structure of a Database Table A database table resembles a spreadsheet in structure but is more powerful due to its integration within a relational database. Here’s a breakdown of a typical database table: Example of a Database Table Consider a simple table that stores information about customers. It could look like this: CustomerID Name Email … Read more
In data science, Data can come in many forms and can describe anything from numbers in a spreadsheet to text in social media posts, images or even audio recordings. Why is Data Important in Data Science? Data is the driving force behind data science. Without data, there would be no insights to draw, no predictions … Read more