Day - 09 | Pandas in Python | pandas numpy | exploratory data analysis in python | data imputation

Veröffentlicht am: 19 Dezember 2023
auf dem Kanal: AI KI PATHSHALA

🚀 *Welcome to AI Ki Pathshala!* 🚀

Timestamp:
00:00:00 - 00:01:35 : Review of Last Session
00:01:36 - 00:04:29 : Another Approach to isolate nulls. It involves using Numpy Universal functions or ufuncs
00:04:30 - 00:14:20 : Sequential Vs Vectorised Operations
00:14:21 - 00:15:55 : np.isnan
00:15:56 - 00:19:55 : Creation of Series using Boolean Data
00:19:56 - 00:25:30 : Calculating the number of NaN values in Series
00:25:31 - 00:32:45 : notnull() and notna()
00:32:46 - 00:37:25 : Equivalence between True and False and the integers 1 and 0 respectively.
00:37:26 - 00:44:17 : Method Resolution Order of bool class
00:44:18 - 00:45:50 : Skill Challenge Questions
00:45:51 - 00:53:47 : Skill Challenge Solutions
00:53:48 - 00:54:57 : Committing code to gitHub
00:54:58 : End Note and Greetings

Telegram Channel : https://t.me/aikipathshala

Telegram Group : https://t.me/+sJdStwuXskVhMTA1

GitHub Repository : https://github.com/anup-byte/Pandas_B...

Basics of Python Playlist :   • Basics of Python

Advance Python Playlist :   • Advance Python

Numpy Playlist :   • Python Numpy Array | Numpy for Data Science

Basics of Git and GitHub Playlist :   • Basics of Git and GitHub

Dive into the fascinating world of Pandas in Python with a fresh perspective! 🐼💡 In this enlightening session, we explore "Another Approach to Isolate Nulls" using Numpy Universal functions (ufuncs) and compare Sequential vs. Vectorised Operations. Uncover the power of `np.isnan`, the creation of Series using Boolean Data, and techniques for calculating the number of NaN values in a Series.

📊 *Key Highlights:*
*Sequential Vs. Vectorised Operations:* Understand the efficiency gains in vectorised operations over sequential ones.

*Using `np.isnan`:* A deep dive into leveraging Numpy universal functions for isolating nulls in your data.

*Creation of Series using Boolean Data:* Learn how to harness Boolean data to create meaningful Series.

*NaN Count Calculation:* Techniques for calculating the number of NaN values in a Series.

*`notnull()` and `notna()`:* Explore these essential Pandas methods for identifying non-null values.

*Equivalence between True/False and 1/0:* Delve into the correlation between boolean values and integers.

*Method Resolution Order of bool class:* Understand the intricacies of method resolution in the bool class.

*Skill Challenge Questions and Solutions:* Test your skills with thought-provoking questions and discover their solutions.

#pandaspythontutorial #datamanipulation #pythonprogramming #aikipathshala #datascience #python #dataanalysis #subscribenow #pandasdataframe #numpy

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