Data Science with Python : NOA

Data science is the process of deriving knowledge and insights from a huge and diverse set of data through organizing, processing and analysing the data. It involves many different disciplines like mathematical and statistical modelling, extracting data from it source and applying data visualization techniques. Often it also involves handling big data technologies to gather both structured and unstructured data. Below we will see some example scenarios where Data science is used.

Chapters Included

Data Science Introduction

Data Science Environment Setup

Pandas

Numpy

Matplotlib

Data Operations

Data cleansing

Processing CSV Data

Processing JSON Data

Processing XLS Data

Relational databases

NoSQL Databases

Date and Time

Data Wrangling

Data Aggregation

Reading HTML Pages

Processing Unstructured Data

word tokenization

Stemming and Lemmatization

Chart Properties

Chart Styling

Box Plots

Heat Maps

Scatter Plots

Bubble Charts

3D Charts

Time Series

Geographical Data

Graph Data

Measuring Central Tendency

Measuring Variance

Normal Distribution

Binomial Distribution

Poisson Distribution

Bernoulli Distribution

P-Value

Correlation

Chi-square Test

Linear Regression