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Data Analysis using NumPy and Pandas

Data Analysis using NumPy and Pandas

Analyze data quickly and easily with Python's powerful numpy and pandas libraries

updated on icon Updated on Apr, 2024

language icon Language - English

person icon DATAhill Solutions Srinivas Reddy

English [CC]

category icon Development,Data Science

Lectures -20

Duration -8 hours

4

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Course Description

If you've spent time in a spreadsheet software like Microsoft Excel, Apple Numbers, or Google Sheets and are eager to take your data analysis skills to the next level, this course is for you!

Data Analysis with Pandas and Python introduces you to the popular Pandas library built on top of the Python programming language.

Pandas is a powerhouse tool that allows you to do anything and everything with colossal data sets -- analyzing, organizing, sorting, filtering, pivoting, aggregating, munging, cleaning, calculating, and more!

I call it "Excel on steroids"!

Over the course of more than 19 hours, I'll take you step-by-step through Pandas, from installation to visualization! We'll cover hundreds of different methods, attributes, features, and functionalities packed away inside this awesome library. We'll dive into tons of different datasets, short and long, broken and pristine, to demonstrate the incredible versatility and efficiency of this package.

Data Analysis with Pandas and Python is bundled with dozens of datasets for you to use. Dive right in and follow along with my lessons to see how easy it is to get started with pandas!

Who this course is for:

  • Data analysts and business analysts
  • Excel users looking to learn a more powerful software for data analysis

Goals

What will you learn in this course:

  • NumPy Introduction
  • Python Numpy Array
  • Indexing & Slicing
  • Statistical Functions, Operators & Random Numbers
  • Introduction Series & DataFrame
  • Date Range & Inspecting Data
  • Indexing & Slicing on DataFrame
  • Concatination & Descriptive Statistics
  • Merging DataFrames
  • Working with Text Data
  • Function Application

Prerequisites

What are the prerequisites for this course?

  • Basic experience with the Python programming language
Data Analysis using NumPy and Pandas

Curriculum

Check out the detailed breakdown of what’s inside the course

Data Analysis using NumPy and Pandas
19 Lectures
  • play icon Introduction 01:09 01:09
  • play icon NumPy Introduction 34:09 34:09
  • play icon Python Numpy Array 22:32 22:32
  • play icon Indexing & Slicing - 1 19:29 19:29
  • play icon Indexing & Slicing - 2 30:21 30:21
  • play icon Statistical Functions, Operators & Random Numbers 20:12 20:12
  • play icon Introduction Series & DataFrame 41:00 41:00
  • play icon Date Range & Inspecting Data 29:36 29:36
  • play icon Indexing & Slicing on DataFrame - 1 30:13 30:13
  • play icon Loc & iloc 31:18 31:18
  • play icon Indexing & Slicing on DataFrame - 2 18:24 18:24
  • play icon Concatenation & Descriptive Statistics 31:54 31:54
  • play icon Merging DataFrames 29:28 29:28
  • play icon Working with Text Data 18:40 18:40
  • play icon Function Application & Loading data in Python 40:33 40:33
  • play icon Loading Data from CSV, Excel & URL 21:24 21:24
  • play icon Data Visualization using Pandas 19:33 19:33
  • play icon What is Data Science 30:42 30:42
  • play icon What is Machine Learning 25:06 25:06

Instructor Details

DATAhill Solutions Srinivas Reddy

DATAhill Solutions Srinivas Reddy

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