EDA using Univariate Analysis | Day 20 | 100 Days of Machine Learning

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The preliminary analysis of data to discover relationships between measures in the data and to gain an insight on the trends, patterns, and relationships among various entities present in the data set with the help of statistics and visualization tools is called Exploratory Data Analysis (EDA).

Exploratory data analysis is cross-classified in two different ways where each method is either graphical or non-graphical. And then, each method is either univariate, bivariate or multivariate.

Uni means one and variate means variable, so in univariate analysis, there is only one dependable variable. The objective of the univariate analysis is to derive the data, define and summarize it, and analyze the pattern present in it. In a dataset, it explores each variable separately. It is possible for two kinds of variables- Categorical and Numerical.

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⌚Time Stamps⌚

00:00 - Intro
00:52 - What is univariate Analysis
02:00 - Types of Data
03:50 - Code Demo on Titanic Dataset
12:05 - Countplot
13:55 - Piechart
15:56 - Working with Numerical Data
19:40 - Distplot
22:05 - Boxplot

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@11:06, looks like there is a change in the API, we need to do
sns.countplot(df, x="Survived")

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shanrock

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devenkapadia

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