Exploratory Data Analysis (EDA) with Python & Pandas | Complete EDA Tutorial | Data Science Project
Learn to perform Exploratory Data Analysis on real-world data using Python Pandas. In this video, we demonstrate how to perform EDA on a dataset (Ozone Weather) with Pandas in Python. Under EDA, you will learn basic data understanding, data preparation, feature understanding (univariate analysis), feature relationships (bivariate and multivariate analysis), and data retrieval from DataFrame using different Pandas useful functions. We will use the following different functions
Jupyter Notebook and DataSet on Github: https://github.com/binary-study/data-...
You can directly run the Notebook on Kaggle without needing to download the notebook and dataset.
You will learn the following in this video:
What is EDA?
Step 1: Basic Data Understanding
Step 2: Data Preparation
Step 3: Univariate Analysis (Feature Understanding )
Step 4: Bivariate and Multivariate Analysis (Feature Relationships)
Step 5: Ask Questions on Data?
Timestamps:
00:00 Intro
02:25 What is EDA?
02:50 Step 0: Data Loading
04:00 Step 1: Basic Data Understanding
08:14 Step 2: Data Preparation
25:00 Step 3: Univariate Analysis (Feature Understanding )
25:55 - Analyzing Categorical Features
28:00 - Analyzing Numerical Features
38:21 Step 4: Bivariate and Multivariate Analysis (Feature Relationships)
38:49 - Numerical vs Numerical
45:45 - Categorical vs Numerical
47:35 - Date vs Numerical (Time series analysis)
48:50 - Categorical vs Categorical (Crosstabs)
50:00 - Grouped Statistics with .groupby()
51:55 Step 5: Ask Questions on Data?
58:20 Outro
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