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Python 🐍 Work With Data

Python 🐍 Work With Data

@python_powerbi

A collection of books and articles on Python and various data manipulation tools. Overview of architecture of business intelligence systems, design and development of BI Reports, data processing in Python Pandas.
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Post #304 659
​​A curated list of chart and dataviz resources that developers may find useful. Focused on relevant and currently active JavaScript charting libraries for different use cases. Ordered alphabetically in each category.
- Commercial Libraries
- Free and Open Source Libraries
- Free Libraries
- Framework-Specific Libraries
- Data Visualization Resources

https://github.com/zingchart/awesome-charting
Post #303 634
DataBank is an analysis and visualisation tool that contains collections of time series data on a variety of topics. You can create your own queries; generate tables, charts, and maps; and easily save, embed, and share them.
https://databank.worldbank.org/databases
databank.worldbank.org Data | DataBank DataBank is an analysis and visualisation tool that contains collections of time series data on a variety of topics where you can create your own queries, generate tables, charts and maps and easily save, embed and share them
Post #297 742

Forwarded from FEDOR BORSHEV

Умение говорить «Нет»

Людей вокруг всегда больше, чем у тебя есть внимания. Дел вокруг больше, чем есть времени. Пет-проектов больше, чем ты можешь сделать.

Очень важно определить свою ёмкость и не брать больше, чем можешь взять: не браться за лишние задачи, не начинать проекты, которые нет времени делать, отказывать коллегам во встречах. Будешь брать лишнее — станешь неэффективным или от чувства вины, или от недосыпа, или от всего вместе. Отупеешь.

Ёмкость может выражаться в количестве активных проектов или во времени, которое ты тратишь на работу. Я вообще определяю на глаз: если кажется, что могу взять больше, — беру, если перегрузился — сливаюсь с лишнего.
Post #296 814
Practical_Data_Analysis_Using_Jupyter_Notebook_Learn_how_to_speak.pdf7.7 MB
Practical Data Analysis Using Jupyter Notebook Learn how to speak the language of data by extracting useful and actionable insights using Python.pdf

What you will learn
• Understand the importance of data literacy and how to communicate effectively using data
• Find out how to use Python packages such as NumPy, pandas, Matplotlib, and the Natural Language Toolkit (NLTK) for data analysis
• Wrangle data and create DataFrames using pandas
• Produce charts and data visualizations using time-series datasets
• Discover relationships and how to join data together using SQL
• Use NLP techniques to work with unstructured data to create sentiment analysis models
• Discover patterns in real-world datasets that provide accurate insights
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