To share my understanding of the concept and techniques I know, I’ll take an example of **House Prices**** **dataset** **which is available on **Kaggle** and try to catch hold of as many insights from the data set using EDA.

Here is a quick overview of the things that you are going to learn in this article:

- Descriptive Statistics
- Outlier Treatment
- Grouping of Data
- Handling missing values in dataset
- Correlation

`import pandas as pd`

import numpy as np

import seaborn as sns

import matplotlib.pyplot as plt

import scipy.stats as stats

Descriptive Statistics helps to describe the basic features of dataset and…

Basics of SQL is mentioned in Part-1 of SQL Approach.

In this article we will be covering various types of

andJoinsSubqueries

We will be working with Hr schema to demonstrate examples.

Multiple Table Queries

**JOINS Clause **is used to join two or more table, bases on a related column between different tables.

Types of Joins

- Simple Joins
- Natural Joins
- Equi Joins
- Non Equi Join
- Self Join
- Left & Right Join
- Inner & Outer Join

t1. column_n, t2.columns_n ,….SELECT

table_1 as t1FROM

table_2 as t2JOIN

t1.column_n = t2.column_n;ON

SQL stands for structured query language A **query** language is a sort of programming language designed to facilitate retrieving specific information from databases .

- SQL is a RDBMS (Relational Database Management Systems) which allows to store, retrieve or manipulate data, but in a more efficient way than DBMS.
- Each
*column*in a table is know as attribute and each*row*in table is know as record/tuple.

*SQL can be devided 5 broad categories as follows;*

Data Definition Language (DDL)

Data Manipulation Language (DML)

Data Query Language (DQL)

Data Control Language (DCL)

Transactional Control Language (TCL)

We will mainly be focusing…

Let’s start with basics and define What regression is? Regression can be defined as a method used to determine the strength and character of relationship between one dependent variable (y) and some other variable known as independent variable (x).

When there’s a single independent variable (x), the method is referred to as simple linear regression. when there are multiple independent variables this method is known as multi linear regression.

The general form of Linear Regression model is:

y = m₁x₁ + m₂x₂ + m₃x₃ + . . . . . + mnxn + c + e

- y = Regressed/ dependent…

Aspiring Data Scientist Linkedin: https://www.linkedin.com/in/vervit-khandelwal/