Analytics Vidhya

SEPTEMBER 4, 2021

This article was published as a part of the Data Science Blogathon Image 1In this blog, We are going to talk about some of the advanced and most used charts in Plotly while doing analysis. All you need to know is Plotly for visualization! The post Performing EDA of Netflix Dataset with Plotly appeared first on Analytics Vidhya.

EDA 324

EDA Clean Data Data Visualization Data Science 324

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. So, without any further ado let’s dive right in. DSD got you covered!

Exploratory Data Analysis 370

Exploratory Data Analysis EDA Data Analysis Data Analysis 370

Dataconomy

AUGUST 16, 2023

Imagine data scientists as modern-day detectives who sift through a sea of information to uncover hidden patterns, trends, and correlations that can inform decision-making and drive innovation. Just like sifting through ancient artifacts, they meticulously clean and refine the data, preparing it for the grand unveiling.

Data Scientist 172

Data Scientist Data Science Machine Learning Machine Learning 172

Pickl AI

DECEMBER 3, 2024

Raw data often contains inconsistencies, missing values, and irrelevant features that can adversely affect the performance of Machine Learning models. Proper preprocessing helps in: Improving Model Accuracy: Clean data leads to better predictions. Matplotlib/Seaborn: For data visualization.

Python 52

Python ML ML Exploratory Data Analysis 52

Pickl AI

MAY 30, 2024

Overview of Typical Tasks and Responsibilities in Data Science As a Data Scientist, your daily tasks and responsibilities will encompass many activities. You will collect and clean data from multiple sources, ensuring it is suitable for analysis. Data Cleaning Data cleaning is crucial for data integrity.

Data Analysis 52

Data Analysis Data Analysis Data Science Exploratory Data Analysis 52

Dataconomy

JULY 28, 2023

Data scientists must decide on appropriate strategies to handle missing values, such as imputation with mean or median values or removing instances with missing data. The choice of approach depends on the impact of missing data on the overall dataset and the specific analysis or model being used.

Power BI 91

Power BI Data Preparation Exploratory Data Analysis Machine Learning 91

Mlearning.ai

APRIL 25, 2023

In this blog, we’ll be using Python to perform exploratory data analysis (EDA) on a Netflix dataset that we’ve found on Kaggle. We’ll be using various Python libraries, including Pandas, Matplotlib, Seaborn, and Plotly, to visualize and analyze the data. The type column tells us if it is a TV show or a movie. df.isnull().sum()

Data Analysis 52

Data Analysis Data Analysis Python Exploratory Data Analysis 52