Data Science Dojo

JANUARY 22, 2023

In this blog, we will discuss exploratory data analysis, also known as EDA, and why it is important. EDA is an iterative process of conglomerative activities which include data cleaning, manipulation and visualization. We will also be sharing code snippets so you can try out different analysis techniques yourself. DSD got you covered!

Exploratory Data Analysis 370

Exploratory Data Analysis EDA Data Analysis Data Analysis 370

Pickl AI

NOVEMBER 4, 2024

Summary: Python for Data Science is crucial for efficiently analysing large datasets. With numerous resources available, mastering Python opens up exciting career opportunities. Introduction Python for Data Science has emerged as a pivotal tool in the data-driven world. As the global Python market is projected to reach USD 100.6

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Pickl AI

APRIL 3, 2025

Exploratory Data Analysis (EDA): Using statistical summaries and initial visualisations (yes, visualisation plays a role within analysis!) Hypothesis Testing: Formally testing assumptions or theories about the data using statistical methods to determine if observed patterns are statistically significant or likely due to chance.

Data Analysis 52

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Pickl AI

MAY 30, 2024

Also Read: Explore data effortlessly with Python Libraries for (Partial) EDA: Unleashing the Power of Data Exploration. Must Check Out: How to Use ChatGPT APIs in Python: A Comprehensive Guide. By checking patterns, distributions, and anomalies, EDA unveils insights crucial for informed decision-making.

Data Analysis 52

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Pickl AI

OCTOBER 14, 2024

Exploratory Data Analysis (EDA) Exploratory Data Analysis (EDA) is an approach to analyse datasets to uncover patterns, anomalies, or relationships. The primary purpose of EDA is to explore the data without any preconceived notions or hypotheses. Python: Offers libraries like Pandas and NumPy for Advanced Data Analysis.

Data Analysis 52

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Becoming Human

MAY 15, 2023

One is a scripting language such as Python, and the other is a Query language like SQL (Structured Query Language) for SQL Databases. Python is a High-level, Procedural, and object-oriented language; it is also a vast language itself, and covering the whole of Python is one the worst mistakes we can make in the data science journey.

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Pickl AI

JULY 25, 2023

With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently. Statistical Analysis: Hypothesis testing, probability, regression analysis, etc.

Data Engineering 52

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