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
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 Joins and Subqueries
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
Simple Join
SELECT t1. column_n, t2.columns_n ,….
FROM table_1 as t1
JOIN table_2 as t2
ON t1.column_n = t2.column_n;
What is SQL ?
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…
