Medium Profile Analyzer for writers using Streamlit and Python

Streamlit-based analytical tool for deep diving into your Medium Profile analytics

I have been writing on Medium for ~3 years now with around 80 blogs around AI & Data Science. As Medium doesn’t pay Indian writers, I never felt Medium Premium to be a dire requirement. Though, I always wished to have a tool that can help me get a deeper dive into my posts than what Medium provides in its free subscription.

Using Streamlit, I recently tried designing such an analytical tool that can help tech & non-tech guys to have intermediate stats alongside some inferences to draw out.

Keeping things simple for now, The app has been divided into 2 parts

The aim of this section is to give aggregated metrics. Below are the sections introduced for now

Given the year of release, this feature displays a timeline for all the blogs released in that year with cover photos & URL

Given a criterion (view, reads, reading length, etc), which blog has the highest value

This section is to understand what & of blogs fulfill a given condition (like 1k+ views, 1k+ reads, 10+ upvotes, etc)

Blog Frequency line plots for analyzing your writing pace across years/months

Word Cloud over blog titles only to get to know what you write most about

Correlation heatmap to understand what factors are affecting your growth/decline. For example, My read % was lower for blogs where the length of the blogs was high. It may be indicative of the fact that people don’t prefer reading long texts

Bi Variate Clustering for important factors. You can add other combinations as well

Distribution of different factors using boxplots

This section focuses more on a particular blog which includes

This sub-section includes a one-on-one comparison between 2 blogs based on factors like total views, total reads, etc. This section also includes a similarity score between the two blogs using

Many of you may face some glitches in the app as it hasn’t been tested on many users. Kindly report any bug on this post or on the git repo. Will be adding some major features in the coming time. Stay tuned !!

By the time, do read out:

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