Welcome to this course on Data Science For Beginners With Python Pandas. Learn how Perform a Many of data operations in Python's popular Pandas library. Link to notebook and dataset: https://github.com/shivamkrishana/internship 🐼 Content 🐼
1 INTRODUCTION
2 GETTING STARTED
3 SERIES PART I
4 SERIES PART II
5 SERIES PART III
6 DATAFRAME PART 1
7 DATAFRAME PART 2
8 DATAFRAMES PART 3
9 DATAFRAME PART 4
10 READING AND VIEWING
11 CORRELATION ANALYSIS
12 DATA CLEANING PART 1
13 DATA CLEANING PART 2
14 PLOTTING WITH PANDAS
15 MERGING
16 JOINING 17 CONCATENATION 18 SELECTION AND UNIQUE
19 APPLY METHOD
20 BASIC OPERATIONS
21 SORTING AND ORDERING
22 DEL KEYWORD
23 HANDLING NULL VALUES
24 PIVOT TABLE
25 BONUS LECTURE Accuracy measures in Data Mining An area that manages, manipulates, extracts, and interprets knowledge from tremendous amount of data. Data scientists are the key to realizing the opportunities presented by big data. #Pandas #DataScienceWithPython #PandasTutorial #DataScienceCourse #DataScienceWithR #PythonPandasTutorial #ProgrammingKnowledge
In this video, we'll dive into the world of Python Pandas, a powerful library for data analysis and manipulation. We'll cover the basics of creating a Pandas dataframe, selecting and filtering data, manipulating columns and rows, and more. First, we'll start with an introduction to Pandas and how it can be used for data analysis tasks. Then, we'll cover the Pandas data structures, including the Series and DataFrame, and how to create and manipulate them. Next, we'll delve into selecting and filtering data with Pandas. We'll show you how to use Boolean indexing to filter your data, how to select specific columns and rows, and how to use the loc and iloc methods to slice and dice your data. We'll also cover data manipulation tasks such as merging, concatenating, and joining dataframes. And we'll show you how to perform common data analysis tasks, such as sorting, grouping, and aggregating data. Finally, we'll wrap up the video with some tips and tricks for working with Pandas, including how to handle missing data and how to apply custom functions to your data. Whether you're a data analyst, data scientist, or just interested in learning more about Python Pandas, this video is a must-watch! So sit back, relax, and get ready to learn!