Instructors: Franklyn Fosu | 11 sections • 14 lectures • 1h 32m total length
Video: MP4 1280x720 44 KHz | English + Sub | Updated 12/2022 | Size: 823 MB

Last updated 6/2018
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.53 GB | Duration: 8h 11m
Get insights and solutions to common data problems while working on real-world datasets using Pandas library

Published 08/2022
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 738 MB | Duration: 15 lectures • 1h 58m

Published 07/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 216 lectures (13h 20m) | Size: 4.11 GB
Learn NumPy & Pandas for data science, data analysis & business intelligence, with practical, hands-on Python projects!

Published 07/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 36 lectures (6h 26m) | Size: 2.53 GB
Learn Pandas since scratch to Ninja!

Published 06/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 16 lectures (1h 19m) | Size: 612.5 MB
Data Analysis with Pandas and Python. Beginners are welcome!

Addison-Wesley - Professional-pandas Data Analysis With Python Fundamentals Tutorial-kEISO
English | Size: 2.22 GB
Category: Tutorial

Reindert-Jan Ekker | Duration: 2h 11m | Video: H264 1280x720 | Audio: AAC 44,1 kHz 2ch | 297 MB | Language: English
Pandas is one of the most popular data analysis libraries for Python. In this course, you will learn how to create a wide range of Descriptions for your data, and how to customize them to make them both attractive and informative for your audience.
At some point when you are working with a dataset, you will want to make the properties of that dataset visible in a graphical way. This is a core skill for every data scientist or data engineer. In this course, Pandas Playbook: Visualization, you'll learn how to create a large variety of beautiful Descriptions with Pandas, one of the most popular data analysis libraries for Python. First, you'll learn the very basics of Descriptionting with pandas, learning how to prepare your dataset for Descriptionting, and how to create common Descriptions like a bar, line, and scatter Description. Next, you will explore matDescriptionlib, the Python library that generates the actual graphics, how this interacts with Pandas, and how to use it correctly. Then, you will go more in-depth and learn about all the ways to customize your Descriptions, including line styles, colors and themes, customizing axes and legends, creating interactive Descriptions, and much more. Finally, you will see a short overview of two other visualization libraries that can be used with Pandas: Seaborn, which is focused on statistical Descriptionting, and Bokeh, which can create interactive visuals for the web. After watching this course, you'll have a deep understanding of all possible ways you can use Pandas to visualize your data. You'll know how to write efficient and clear code that creates beautiful Descriptions, following best practices. This course will also make you more proficient in exploring datasets and communicating your results with others.

| Duration: 2h 15m | Video: H264 1280x720 | Audio: AAC 44,1 kHz 2ch | 292 MB | Language: English
Pandas is one of the most popular software packages for data analysis. This course focuses on the core functionalities of Pandas for data wrangling, teaching you how to tackle everyday tasks for a data analyst, or data scientist.
Pandas is not just one of the most popular software packages for data analysis, it is also, without a doubt, the most convenient and fun way to work with your data. In this course, Pandas Playbook: Manipulating Data, you will cover the most important core functionalities of Pandas, focusing on the core functionalities of the two main Pandas classes: the DataFrame and the Series. First, you will take a look at a new dataset and try to get a feeling for it - how many rows and columns are there? What datatypes does it consist of? You will do some basic statistical exploration as well. Then, you'll focus on getting information out of your dataset. Basically, it's about asking the right questions and drilling down into your dataset. Finally, you will learn how to clean and transform your data. Here, you will see how to run Python functions against our data, including functions we write ourselves by using a very cool and powerful feature called groupby() - changing the structure of our columns and rows, and combining multiple dataframes into one. After watching this course, you will be ready for just about any data wrangling job that you might come across.

Paweł Kordek | Duration: 1h 20m | Video: H264 1280x720 | Audio: AAC 44,1 kHz 2ch | 199 MB | Language: English
Quick and expressive data analysis requires good tools and knowledge of them. In this course, you'll explore the world of data science by learning core Pandas functionalities, including its IO capabilities, Descriptionting methods, and DataFrames.
As an individual working with data, from business analysts to data scientists, you desire a quick feedback loop that enables you to materialize and easily visualize your ideas. Time spent on developing and debugging programs or clicking around spreadsheets is often wasted. In this course, Pandas Fundamentals, you'll learn how to quickly read the data, perform desired analysis, and output it in a neat format along with pleasant Descriptions. First, you'll explore data input and output. Next, you'll discover how to index and filter your data. Finally, you'll delve into how to work with groups, along with creating Descriptions. After finishing this course, you'll have the necessary knowledge to manipulate data in basic forms, and be able to utilize your time more efficiently when figuring out how to transform your data to reach the desired effect. Software required: Anaconda Python.