Python基础与数据分析：NumPy & Pandas完全指南

2024年最新课程，从零学习Python语法、NumPy数组与Pandas数据处理，掌握数据清洗、过滤与合并实战技能，适合无编程经验者快速入门数据分析。

原始标题：Python Basics + Data Science : Numpy & Pandas Guide

Published 12/2024
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.47 GB | Duration: 4h 43m

From Fundamentals to Real-World Applications: Master Python, NumPy, and Pandas for Data Analysis

What you’ll learn
Learn Python syntax, variables, loops, functions, and error handling to write efficient code for basic programming tasks
nderstand NumPy arrays, slicing, reshaping, and vectorized operations for efficient numerical computing with large datasets.
Gain hands-on experience with Pandas for data cleaning, filtering, grouping, and merging datasets in Python.
Solve coding challenges and build real-world projects using Python, NumPy, and Pandas to showcase skills to potential employers.

Requirements
No programming experience required, you will get to learn everything in course

Overview
Section 1: Introduction to python and environment

Lecture 1 Introduction

Lecture 2 Online IDE’S

Lecture 3 Offline IDE’s and environment

Section 2: Comments, Indentation and Syntax

Lecture 4 Basic Synatx

Lecture 5 Comments

Lecture 6 Indentation

Section 3: Operators, Variables and Data Types

Lecture 7 Keywords and Identifiers

Lecture 8 Types of operators

Lecture 9 Operator (cont.)

Lecture 10 Data types and type casting

Section 4: Conditional statement and loops

Lecture 11 If-else condition

Lecture 12 For and while Loop

Section 5: Function and modules

Lecture 13 Types of function

Lecture 14 global and local scope

Section 6: Basic Data Structures

Lecture 15 Lists

Lecture 16 Tuples

Lecture 17 Dictionaries

Lecture 18 Lists vs tuples vs dictionaries

Section 7: Introduction to Numpy and pandas

Lecture 19 Introduction to Numpy

Lecture 20 Functions in numpy

Lecture 21 Introduction to pandas

Lecture 22 Functions in pandas

Lecture 23 creating new dataframe and cleaning data

Aspiring data analysts, data scientists, and machine learning engineers who want to get hands-on experience with Python, NumPy, and Pandas.,Students or professionals seeking to expand their skill set and pursue a career in data science, programming, or related fields.,Developers transitioning to Python who need to strengthen their understanding of data manipulation and numerical computing libraries.,Anyone interested in solving real-world problems by working with data through coding exercises and projects from top MNC companies.,Anyone interested in data analysis who prefers a hands-on learning approach with coding challenges and practical projects,Students in STEM fields who want to improve their coding and data manipulation skills, preparing for internships or future roles in tech.