JSON Visualizer

Opening a JSON file and getting an understanding of its structure can be pretty daunting sometimes, especially if it involves a huge amount of data. This program helps visualise the tree of the JSON file. It can be used to get some useful information like - structure, depth (number of levels in heierarchy). It presents all this in a beautiful and scalable pictorial format

• Python
• SVG
• HTML
• CSS

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Telecom churn case study

The case study was regarding customer churn prediction in Telecom industry. There are 7000+ entries and 20+ parameters. The data includes a column to show whether the customer has churned or not. Based on this, a model needs to be created to predict the churn probability of a given customer. Data cleanup was performed. This involved checking outliers, converting text entries to numeric etc.. Simple Exploratory Data Analysis (EDA) was performed. A suitable model was built after splitting the data into test and train datasets. Feature elimination was performed using RFE and VIF in multiple iterations. Once we reached satisfactory results on train case, then the model was applied to the test case. Eventually the results that were achieved are: Accuracy=73.54%, Sensitivity=74.2%, Specificity=73.3%

• Python
• Pandas
• Scikit Learn
• Seaborn

Code

Chess case study

This dataset was taken from kaggle. It has a lot of useful columns like who won the game, time taken, number of moves, opening type etc... Exploratory Data analysis was done on the dataset and visualisation was done in seaborn. Created appropriate columns like the game format (classified the game as Bullet, Rapid, Classical) and performed analysis based on that

• Python
• Pandas
• Seaborn

Code

Know your Solar System

imply reading data does not give a perspective. So, visualise it here. Made in pygame.Compare facts like sizes, rotation speeds, revolution speeds, speed of travel in space (basically a drag race of all planets) in a fun way:

• Python
• PyGame

Code