Being from an operations management background, monitoring performance was always a priority task in my portfolio. In this blog post Just tried to collate different representation styles I had often come across for measuring and monitoring performance. At the bottom of the blog, there is a voting app with a simple pie chart dashboard for displaying voter percentage distribution for the first three choices.
• live link to the app https://datarabbit.in/blog/blog/TargetVsAchievements
• app author’s name with a link to their LinkedIn profile (or any other resume platform)
Author Name: Ashwaghosh Wankhade
Linkedin: https://www.linkedin.com/in/ashwaghoshwankhade/
• app title (under 35 characters if possible)
Target Vs Achievement
• app description (under 105 characters if possible)
It is a blog which discusses possible alternatives which could be used to display Target assigned Vs Target Achieved. In this blog post, all charts are interactive dash apps with all default options. At the end of a blog, there is an option to post a vote for your favourite representation type.
• public GitHub repo with the app’s code (not mandatory but highly encouraged)
Not created, if anyone is interested in finding out; I would like to create a new repository and share it with them.
live link to the app:CAS OpenData Name: Xin Yu LInkedIN: https://www.linkedin.com/in/xinyu2/ App title: COVID-19 Antibody Therapeutics Tracker Description: As the COVID-19 pandemic is the global healthcare crisis, scientists worldwide are collaborating to prevent or treat COVID-19. Antibody therapeutics hold enormous promise for treatment of COVID-19. Chinese Antibody Society is collaborating with our partner The Antibody Society to track the antibody-based therapeutics targeting COVID-19, to contribute our expertise to the globally joint efforts against the pandemic. In connection with the collaboration, The Antibody Society has published a “Coronavirus in the Crosshairs” series of articles addressing different aspects of therapeutics against COVID-19, and is continuous publishing new information and analysis. Publication in peer-reviewed journal: COVID-19 antibody therapeutics tracker: a global online database of antibody therapeutics for the prevention and treatment of COVID-19 - PubMed
app description (under to 105 characters if possible): Problem to Solve: Based on my experience as a Escalations representative, I believe there is an issue with customer cancellations. My goals is to explore the data and try to understand customer behavior. Assumption: customers are cancelling due to extended cleanup start times from purchase date. To prove this hypothesis, will need to show as date difference decreases, tenure should increase. Limitation: I do not have access to 2022 data.
App Description:
– Uses Plotly and Dash to visualize ER wait data via line and violin charts.
– Interactive plot features such as zooming, panning, computing rolling average, dark mode/theme.
– Data is modeled using least squares optimization curve fitting.
App Description:
Statistics are plotted using Plotly and Dash on each type of bingo win, e.g. specific row, column, diagonals or corners. Interactive features include dark mode and selecting detail level of the histograms and pie charts.
I would like to submit 4 web apps that we/I made.
I have made more but will only be submitting these.
I am very thankful for a library like Dash to have existed and to have made it so convenient and accessible to develop web apps, for all sorts of purposes. Thank you to the devs <3.
Title
Mutation Prediction in Breast Cancer Patients
Description
This is a webapp to predict the probability of mutation in Breast Cancer patients from an Indian cohort. We can predict probability for 3 broad categories of mutations: any gene mutations (general), pathogenic gene mutations (brca1/2, chek, etc.), VUS gene mutations (variants of unknown significance)
An extension tool simplifying the LiftOver tool and greatly increasing convenience by not having to download and open a .bed file each time. Increased QoL.
During the covid-19 pandemic, bioRxiv had become a popular platform amongst researchers to share their work. This plays a critical role in speeding up the research related to COVID-19. This dashboard helps in tackling the surge in number of research papers, by providing researchers with necessary information. We have performed psychometric analysis on the twitter data collected for each paper and presented our findings in the form of different interactive plots. Also, we have used this data to sort the papers on different grounds.
Live link to the app:https://report.thermoplan.ch App author’s name: Thermoplan AG App title: Product Environmental Report App description: An interactive Plotly app that shows the environmental impact of Thermoplan’s coffee machines in full transparency. Public github repo: not available yet
Hi, here is my Dash app: https://databora.pythonanywhere.com/
Author: Borivoj Grujicic
LinkedIn: https://www.linkedin.com/in/borivojgrujicic/
App title: Complete Business Intelligence
Description: This app provides insights into Sales, Logistics and Production. These are all real world needed calculation and analytics that are necessary for any business to improve their operations.
app title: Exploring Eye-tracking data with MNE-Python
app description: MNE-Python is a widely used Python package for analyzing physiological signals, mainly MEG, EEG, fNIRS, and Eye-tracking. By default, MNE’s visualization functions use a QT framework, meaning you can only visualize your data on your local computer, making sharing your data with others difficult. This dash app provides an example for plotting 2D data from MNE-Python in a dash framework.
Here is a second submission of mine. A very different type of app compared to most.
Metabolomics Sample Metadata Standardizer
Live link to the app:http://samplemetadatastandardizer.us-west-2.elasticbeanstalk.com/ App author’s name: Parker Bremer, UC Davis Fiehnlab App title: Metabolomics Sample Metadata Standardizer App description short: This app curates sample metadata (species, organ, disease, gene, time series, etc.). App description long: Metabolomics needs to prove reproducibility to obtain clinical value on the same level as genomics, etc. One way to facilitate this is to enable programmatic metaanalysis by making sample descriptions standardized. This app does two things. 1) Users can generate a form to describe samples in their metabolomics study. 2) They can submit that form and be walked through a set of steps to curate those data. At the end, users are given a curated version of their submission and that same data is sent to other software for downstream analysis. Public github repo: [GitHub - plbremer/sample_ingester_frontend]
app description (under to 105 characters if possible): Problem to Solve: Based on my experience as a Escalations representative, I believe there is an issue with customer cancellations. My goals is to explore the data and try to understand customer behavior. Assumption: customers are cancelling due to extended cleanup start times from purchase date. To prove this hypothesis, will need to show as date difference decreases, tenure should increase. Limitation: I do not have access to 2022 data.
