Franccesco Orozco
Chief Data Scientist @ Traction Tools
Love all the things data. Python developer and blogger. Fan of self-improvement.
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Hello, I'm using the scheduling feature to execute multiple notebooks doing:
jupyter nbconvert --execute --inplace my_notebook.ipynb
But some of them have SQL tables and it gives me an error. Does anyone know a workaround?
jupyter nbconvert --execute --inplace my_notebook.ipynb
But some of them have SQL tables and it gives me an error. Does anyone know a workaround?
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Hello, when setting up PSQL integration, if I click in "Test Connection," it reports that the connection failed. However, when I run the SQL query, it is run successfully.
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I have scheduled three notebooks that execute at 2 AM, but they've triggered again at 10 AM (CST timezone - America/Managua).
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Something we love to do at Traction Tools is to drive actionable insights. We love to empower our people to make better decisions using data, and in this ocasion I got permission to publish an internal whitepaper that describes the process that we use to categorize our users using Bronze, Silver, and Gold labels. Hopefully this will help you as well.
This helps us empower our marketing campaigns, and also helps people to understand the spending behaviors of our customers. It's a great tool to identify areas of opportunity that sales, support, and marketing teams can use to help scale their processes
This will helps you understand:
This helps us empower our marketing campaigns, and also helps people to understand the spending behaviors of our customers. It's a great tool to identify areas of opportunity that sales, support, and marketing teams can use to help scale their processes
This will helps you understand:
- Retention behaviors and spending habits by cohorts
- Calculating customers Recency, Frequency, and Monetary Values
- Creating segments and developing a point system using RFM scores
- Discovering growing opportunities around clusters with low RFM scores
- Labeling our customers using Bronze, Silver, and Gold categories
- Train a K-Means model to cluster our users based on RFM values
The whitepaper is also extensively documented. If you're wondering how do we apply Deepnote to a well-stablished business then this is how. Many of the things you'll see here are taken from a lot of sources, like Datacamp, which we use to train our analysts. However, I made this one 😄
Am I late to the competition? I hope not 🙌
Customer Segmentation and Cohort Analysis @ Traction Tools
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You know, just noticing the little things ❤️
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I'm confused with the CPU metric. It jumps from 0% to 100%, and sometimes it gets stuck at 100% with Pro machines. It makes me think that I'm using 100% of all 16 vCPUs.
How is that metric calculated? I think it would be ideal to have better CPU metrics to decide if I should use a Standard, Pro, or Performance machine. Thank you 🙂
How is that metric calculated? I think it would be ideal to have better CPU metrics to decide if I should use a Standard, Pro, or Performance machine. Thank you 🙂
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I was trying out the extension Dark Reader, and I just thought that a dark theme would look great in Deepnote. Nothing or priority, of course, just a thought 🙂
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There are some notebooks which I can't assign them a category. Even if I create a new one.
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When sharing a cell via the option "Share cell output," if the data frame is collapsed, then the option"Expand rows" doesn't work.
