Python

Amazon AWS Transcribe used to get 2020 presidential debate #1 speaker segments

TLDR: I used Amazon Transcribe to transcribe the first presidential debate audio that included timestamps for each word, to create the following speaker timeline visualization (created using a Plotly timeline chart). Click image to view full size visualization. After watching the US 2020 Presidential Debate #1  I was curious to see if there was an …

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Amazon AWS Textract – WHO “Draft landscape of COVID-19 candidate vaccines” – convert PDF to csv

TLDR: I extracted text from the WHO’s vaccine candidate PDF file using AWS Textract and made text into a set of interactive web pages . View the AWS Textract PDF extract output csv files in this Github repository and view and interact with the web pages here. The World Health Organization (WHO) maintains a regularly …

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Periodic chart elements by origin from SVG using Python

This cool periodic chart of the elements shows source / origin of the chemical elements. Source: Wikipedia created by Cmglee It was really interesting to learn that elements may be created from more than one source/origin which are listed below: Big Bang fusion Exploding white dwarfs Exploding massive stars Cosmic ray fission Merging neutron stars …

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Retrieve and process Environment Canada hydrometric and climate data using Python

Recently needed to get flow and level data for a watercourse hydrological station as well as regional precipitation data for relevant location(s) upstream within the watershed of the station. The objective was to combine two decades of watercourse flow and level with regional watershed precipitation data into a single set of analysis and reporting. Environment …

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Plotly Express Python remove legend title

Plotly.py 4.5, Plotly Express no longer puts the = in trace names, because legends support titles (source). Prior to Plotly.py 4.5, I had used this ‘hover_data’ trick to remove the ‘=’ from the legend trace names. hover_data=[‘gain_loss’]).for_each_trace(lambda t: t.update(name=t.name.split(“=”)[0]) However now with Plotly.py 4.5, I want to remove the legend title. The new trick to …

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