|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/complete-python-pandas-tutorial-in-hindi-with-notes/
课程评论：没有评论
课程名称：完整的Python Pandas教程（印地语）（含笔记） 课程概述：Pandas是一种用于处理数据集的Python库。它具有分析、清理、探索和操纵数据的功能。“Pandas”这个名称既与“面板数据”（Panel Data）有关，也与“Python数据分析”（Python Data Analysis）有关，该库由Wes McKinney于2008年创建。 为什么使用Pandas？Pandas可以让我们分析大数据，并基于统计理论得出结论。Pandas能够清理混乱的数据集，使其可读且相关，而相关数据对于数据科学至关重要。 Pandas能做什么？Pandas为您提供有关数据的答案，例如：两个或多个列之间是否存在相关性？平均值、最大值和最小值分别是多少？Pandas还能够删除不相关的行或包含错误值（如空值或NULL值）的行，这就是数据清理的过程。Pandas主要用于数据分析及对DataFrame中表格数据的操作。Pandas允许从多种文件格式导入数据，如逗号分隔值（CSV）、JSON、Parquet、SQL数据库表或查询，以及Microsoft Excel。Pandas支持多种数据操作，如合并、重塑、选择、数据清理以及数据整理等功能。Pandas的开发引入了许多与R编程语言中DataFrame工作类似的特性。Pandas库的构建基于另一个库NumPy，该库专注于高效处理数组，而不是DataFrame的特性。 讲师介绍：Sharad Khare是一名数据智能科学家和欺诈分析师，拥有超过9年的全球安全和调查领域的法律经验，涉及内容政策、反滥用操作、审计知识产权违规、反欺诈操作和调查。他还担任不同教育机构的外部邀请教师，教授HTML、PHP、R语言、MYSQL、Python、JavaScript和数据科学。
What is Pandas?Pandas is a Python library used for working with data sets.It has functions for analyzing, cleaning, exploring, and manipulating data.The name "Pandas" has a reference to both "Panel Data", and "Python Data Analysis" and was created by Wes McKinney in 2008.Why Use Pandas?Pandas allows us to analyze big data and make conclusions based on statistical theories.Pandas can clean messy data sets, and make them readable and relevant.Relevant data is very important in data science. What Can Pandas Do?Pandas gives you answers about the data. Like:Is there a correlation between two or more columns?What is average value?Max value?Min value?Pandas are also able to delete rows that are not relevant, or contains wrong values, like empty or NULL values. This is called cleaning the data.Pandas is mainly used for data analysis and associated manipulation of tabular data in Dataframes. Pandas allows importing data from various file formats such as comma-separated values, JSON, Parquet, SQL database tables or queries, and Microsoft Excel. Pandas allows various data manipulation operations such as merging, reshaping, selecting, as well as data cleaning, and data wrangling features. The development of pandas introduced into Python many comparable features of working with DataFrames that were established in the R programming language. The pandas library is built upon another library NumPy, which is oriented to efficiently working with arrays instead of the features of working on DataFrames.About the Instructor:Sharad Khare is Data Intelligence Scientist and Fraud Analyst with 9+ years of Legal experience in the Global Safety and Investigative sectors with content policy, anti-abuse operations, Audit Intellectual Property violations, Anti-Fraud Operations and Investigation.He is also the External Invitee Faculty of different different Education institutions for tutoring HTML, PHP, R Language, MYSQL, Python, JavaScript and Data science.
