Master Pandas and Python for Data Handling [2025]
Год выпуска: 3/2024
Производитель: Udemy
Сайт производителя:
https://www.udemy.com/course/master-pandas-and-python-for-data-handling/
Автор: Henrik Johansson
Продолжительность: 21h 47m 58s
Тип раздаваемого материала: Видеоурок
Язык: Английский
Субтитры: Английский
Описание:
What you'll learn
- Master Python programming with Python’s native data structures, data transformers, functions, object orientation, and logic
- Master the Pandas library for Advanced Data Handling
- Perform Advanced Data Handling
- Manipulate data and use advanced multi-dimensional uneven data structures
- Use Python’s advanced object-oriented programming and make your own custom objects, functions and how to generalize functions
- Use the language and fundamental concepts of the Pandas library and to handle all aspects of creating, changing, modifying, and selecting Data from a Pandas D
- Use file handling with Pandas and how to combine Pandas DataFrames with Pandas concat, join, and merge functions/methods
- Perform advanced data preparation
Requirements
- The four ways of counting (+-*/)
- Everyday experience using a computer with either Windows, MacOS, iOS, Android, ChromeOS, or Linux is recommended
- Access to a computer with an internet connection
- Programming experience is not needed and you will be taught everything you need
- The course only uses costless software
- Walk-you-through installation and setup videos for Cloud computing and Windows 10/11 is included
Description
This two-in-one video course will teach you to
master Python 3,
Pandas 2-3, and
Data Handling.
Python 3 is one of the most popular programming languages in the world, and Pandas 2 and future 3 is the most powerful, efficient, and useful Data Handling library in existence.
You will learn to master Python's native building blocks and powerful object-oriented programming. You will design your own advanced constructions of Python’s building blocks and execute detailed Data Handling tasks with Python.
You will learn to master the Pandas library and to use its powerful Data Handling techniques for advanced Data Science, Statistics, and Machine Learning Data Handling tasks. The Pandas library is a fast, powerful, flexible, and easy-to-use open-source data analysis and data manipulation tool, which is directly usable with the Python programming language.
You will learn to:
- Master Python programming with Python’s data structures, data transformers, functions, object orientation, and logic
- Use and design advanced Python constructions and execute detailed Data Handling tasks with Python incl. File Handling
- Use Python’s advanced object-oriented programming and make your own custom objects, functions and how to generalize functions
- Manipulate data and use advanced multi-dimensional uneven data structures
- Master the Pandas library for Advanced Data Handling
- Use the language and fundamental concepts of the Pandas library and to handle all aspects of creating, changing, modifying, and selecting Data from a Pandas DataFrame object
- Use file handling with Pandas and how to combine Pandas DataFrames with Pandas concat, join, and merge functions/methods
- Perform advanced data preparation including advanced model-based imputation of missing data and the scaling and standardizing of data
- Make advanced data descriptions and statistics with Pandas. Rank, sort, cross-tabulate, pivot, melt, transpose, and group data
- [Bonus] Make advanced Data Visualizations with Pandas, Matplotlib, and Seaborn
- Perform Advanced Data Handling
- [Cloud computing]: Use the Anaconda Cloud Notebook (Cloud-based Jupyter Notebook). Learn to use Cloud computing resources.
- Option: To use the Anaconda Distribution (for Windows, Mac, Linux)
- Option: Use Python environment fundamentals with the Conda package management system and command line installing/updating of libraries and packages – golden nuggets to improve your quality of work life.
- And much more…
This course is an excellent way to learn to master Python, Pandas and Data Handling! Data Handling is the process of making data useful and usable for data analysis. Most Data Scientists and Machine Learning Engineers spends about 80% of their working efforts and time on Data Handling tasks.
Being good at Python, Pandas, and Data Handling are extremely useful and time-saving skills that functions as a force multiplier for productivity.
This course is designed for anyone who wants to:
- learn to Master Python 3 from scratch or the beginner level
- learn to Master Python 3 and knows another programming language
- reach the Master - intermediate Python programmer level as required by many advanced Udemy courses in Python, Data Science, or Machine Learning
- learn Data Handling with Python
- learn to Master the Pandas library
- learn Data Handling skills that work as a force multiplier and that they will have use of in their entire career
- learn advanced Data Handling and improve their capabilities and productivity
Requirements:
- Everyday experience using a computer with either Windows, MacOS, iOS, Android, ChromeOS, or Linux is recommended
- Access to a computer with an internet connection
- Programming experience is not needed and you will be taught everything you need
- The course only uses costless software
- Walk-you-through installation and setup videos for Cloud computing and Windows 10/11 is included
This course is the course we ourselves would want to be able to enroll in if we could time-travel and become new students. In our opinion, this course is the best course to learn to Master Python, Pandas, and Data Handling.
Enroll now to receive 25+ hours of video tutorials with manually edited English captions, and a certificate of completion after completing the course!
Who this course is for:
- Anyone who wants to learn to Master Python 3 from scratch or the beginner level
- Anyone who wants to learn to Master Python 3 and knows another programming language
- Anyone who wants to reach the Master - intermediate Python programmer level as required by many advanced Udemy courses in Python, Data Science, or Machine Learning
- Anyone who wants to learn Data Handling with Python
- Anyone who wants to learn to Master the Pandas library
- Anyone who wants to learn Data Handling skills that work as a force multiplier and that they will have use of in their entire career
- Anyone who wants to learn advanced Data Handling and improve their capabilities and productivity
Формат видео: MP4
Видео: avc, 1280x720, 16:9, 30.000 к/с, 520 кб/с
Аудио: aac lc, 48.0 кгц, 128 кб/с, 2 аудио
MediaInfo
General
Complete name : D:\2\Udemy - Master Pandas and Python for Data Handling [2025] (3.2024)\3. Master Pandas for Data Handling\24. Pandas Data Description II Sorting and Ranking.mp4
Format : MPEG-4
Format profile : Base Media
Codec ID : isom (isom/iso2/avc1/mp41)
File size : 126 MiB
Duration : 26 min 51 s
Overall bit rate : 656 kb/s
Frame rate : 30.000 FPS
Writing application : Lavf59.27.100
Conformance errors : 2
read : Yes
General compliance : Element size 2065855584 is more than maximal permitted size 10232 (offset 0x7E16691)
MPEG-4 : Yes
General compliance : File size 132222601 is less than expected size 2198067953 (offset 0x7E16691)
Video
ID : 1
Format : AVC
Format/Info : Advanced Video Codec
Format profile : Main@L3.1
Format settings : CABAC / 4 Ref Frames
Format settings, CABAC : Yes
Format settings, Reference frames : 4 frames
Format settings, GOP : M=4, N=60
Codec ID : avc1
Codec ID/Info : Advanced Video Coding
Duration : 26 min 51 s
Bit rate : 520 kb/s
Nominal bit rate : 3 000 kb/s
Maximum bit rate : 3 000 kb/s
Width : 1 280 pixels
Height : 720 pixels
Display aspect ratio : 16:9
Frame rate mode : Constant
Frame rate : 30.000 FPS
Color space : YUV
Chroma subsampling : 4:2:0
Bit depth : 8 bits
Scan type : Progressive
Bits/(Pixel*Frame) : 0.019
Stream size : 99.8 MiB (79%)
Writing library : x264 core 164 r3095 baee400
Encoding settings : cabac=1 / ref=3 / deblock=1:0:0 / analyse=0x1:0x111 / me=umh / subme=6 / psy=1 / psy_rd=1.00:0.00 / mixed_ref=1 / me_range=16 / chroma_me=1 / trellis=1 / 8x8dct=0 / cqm=0 / deadzone=21,11 / fast_pskip=1 / chroma_qp_offset=-2 / threads=22 / lookahead_threads=3 / sliced_threads=0 / nr=0 / decimate=1 / interlaced=0 / bluray_compat=0 / constrained_intra=0 / bframes=3 / b_pyramid=2 / b_adapt=1 / b_bias=0 / direct=1 / weightb=1 / open_gop=0 / weightp=2 / keyint=60 / keyint_min=6 / scenecut=0 / intra_refresh=0 / rc_lookahead=60 / rc=cbr / mbtree=1 / bitrate=3000 / ratetol=1.0 / qcomp=0.60 / qpmin=0 / qpmax=69 / qpstep=4 / vbv_maxrate=3000 / vbv_bufsize=6000 / nal_hrd=none / filler=0 / ip_ratio=1.40 / aq=1:1.00
Codec configuration box : avcC
Audio
ID : 2
Format : AAC LC
Format/Info : Advanced Audio Codec Low Complexity
Codec ID : mp4a-40-2
Duration : 26 min 51 s
Source duration : 26 min 51 s
Bit rate mode : Constant
Bit rate : 128 kb/s
Channel(s) : 2 channels
Channel layout : L R
Sampling rate : 48.0 kHz
Frame rate : 46.875 FPS (1024 SPF)
Compression mode : Lossy
Stream size : 24.6 MiB (19%)
Source stream size : 24.6 MiB (19%)
Default : Yes
Alternate group : 1