Analytics Vidhya

JULY 7, 2020

The post Tableau Tip: Visualize a Single Value Against Others appeared first on Analytics Vidhya. Introduction How often have we all tried to compare a value against a range, with unsatisfying results? Excel is the most common tool for.

Tableau 313

Tableau Analytics Analytics EDA 313

ODSC - Open Data Science

FEBRUARY 24, 2023

There are many well-known libraries and platforms for data analysis such as Pandas and Tableau, in addition to analytical databases like ClickHouse, MariaDB, Apache Druid, Apache Pinot, Google BigQuery, Amazon RedShift, etc. These tools will help make your initial data exploration process easy.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Analytics Vidhya

NOVEMBER 30, 2020

This article was published as a part of the Data Science Blogathon. Overview In this article, I will share my thoughts on the below. The post Interpreting P-Value and R Squared Score on Real-Time Data – Statistical Data Exploration appeared first on Analytics Vidhya.

Data Science 291

Data Science Analytics Analytics EDA 291

Dataconomy

JULY 28, 2023

Exploratory data analysis (EDA) Before preprocessing data, conducting exploratory data analysis is crucial to understand the dataset’s characteristics, identify patterns, detect outliers, and validate missing values. EDA provides insights into the data distribution and informs the selection of appropriate preprocessing techniques.

Power BI 91

Power BI Data Preparation Exploratory Data Analysis Machine Learning 91

Pickl AI

APRIL 3, 2025

Exploratory Data Analysis (EDA): Using statistical summaries and initial visualisations (yes, visualisation plays a role within analysis!) EDA: Calculate overall churn rate. It involves handling missing values, correcting errors, removing duplicates, standardizing formats, and structuring data for analysis.

Data Analysis 52

Data Analysis Data Analysis Data Visualization EDA 52

Pickl AI

APRIL 21, 2025

Exploring the Data (Exploratory Data Analysis – EDA) Digging into the cleaned data to understand its basic characteristics, find patterns, identify trends, and visualize relationships. This often takes up a significant chunk of a data scientist’s time. Think graphs, charts, and summary statistics.

Big Data 52

Big Data Big Data Data Science Machine Learning 52

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. Clustering: Grouping similar data points to identify segments within the data.

Data Analysis 52

Data Analysis Data Analysis EDA Data Mining 52