Data Analysis Program

The Data Analysis Program is a desktop application developed with PyQt5, Pandas, Seaborn, and Matplotlib to facilitate data exploration, analysis, and visualization. This program provides a user-friendly interface for loading datasets, exploring their structures, generating descriptive statistics, conducting correlation analysis, and more.

Features

Data Loading and Exploration

• Load Datasets:

  • Seaborn Datasets: Choose a sample dataset from the Seaborn datasets library.
  • Local Datasets: Load a local dataset from your device by leaving the combo box as "None".

• Inspect Dataset:

  • View the head and tail of the dataset.
  • Display data types of each column.
  • Show the sum of null values for each column and fill NA values. Options to ignore "0" values and encode boolean values.
  • View dataset's statistical values.
  • Get information for each column.

Data Editing for Machine Learning

• Prepare Data:

  • Fill null values and encode non-numeric data types to make the dataset machine learning-ready.

• Basic Machine Learning Model:

  • Create a basic RandomForest model and save it for future predictions.
  • Predict outcomes by typing in data or getting random data. Edit random data and predict.

Column Categorization

• Categorize Columns:
  • Identify categorical and numerical columns, distinguishing between high-cardinality categorical columns and numerical columns treated as categorical.

Data Analysis

• Target Variable Summary:

  • Generate summaries of the target variable grouped by other columns, with visualization options.

• Correlation Analysis:

  • Perform correlation analysis on numerical columns and visualize the correlation matrix as a heatmap.

• Column Summary:

  • Provide insights into categorical and numerical columns with count plots, histograms, and percentage summaries.