There are a lot of crime data analyses floating around, but our pick this week not only analyzes the
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November 6 · Issue #162 · View online |
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There are a lot of crime data analyses floating around, but our pick this week not only analyzes the data, but invites the reader to make it better by publishing a Deepnote Notebook for further data analysis. We also have an interesting piece on how to avoid dunders in Python, and a good resource listing this Winter’s data visualization conferences. Stay Healthy!
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Fight San Francisco Crime with fast.ai and Deepnote | by Anthony Agnone | Nov, 2020 | Towards Data Science
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Extracting and joining data from multiple data sources with Athena Federated Query | Amazon Web Services
Athena federated query allows Lambda data connectors to run queries against multiple AWS data sources, including ElasiCache, DynamoDB, Aurora MySQL and Redshift. This piece shows an example with four different data sources.
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How to Make Inserts Into SQL Server 100x faster with Pyodbc | by Anna Anisienia | Oct, 2020 | Towards Data Science
A straightforward explanation of the fast_executemany option in Pyodbc, which allows in-memory acceleration of SQL Server inserts.
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Dunderless Python. This story is about improving your code quality and ways to reduce boilerplate when working with python. | Towards Data Science
How to make your Python code more readable, which means creating a class or a data container in an easy and straightforward way, without boilerplate or effort to write or read object protocols (__init__ = dunder init dunder).
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The Dos and Don’ts of Imputation. By E. Zuccarelli | Towards Data Science
Missing data is a problem often present in real-life datasets, Imputation helps to fill the missing information and achieve better performance. This piece names three common practices to avoid, and recommends three imputations for missing data.
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Data Visualization Conferences: Winter 2020–2021 | by Mollie Pettit | Nightingale | Oct, 2020 | Medium
If you’re looking for a conference, this is the document for you – updated regularly by the author. She’s also taking recommendations for conferences if you have any.
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An Ultimate Cheat Sheet for Data Visualization in Pandas | by Rashida Nasrin Sucky | Oct, 2020 | Towards Data Science
“Ultimate” is a big claim, but this piece at least comes close to living up to it by having an exhaustive list of visualizations, with code examples.
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These ArcGIS StoryMaps collections will inspire you
Many, many StoryMaps covering a wide variety of topics, which shows off the StoryMap platform as well as providing inspiration for your visualization project.
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A Day in the Life of a Netflix Content Analytics Engineer | Netflix TechBlog
Rocio Ruelas of Netflix LA shares her perspective of the projects, technical skills, and day-to-day of working in the Content analytics and metrics research space.
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