Format of Excel Sheet


  • Row A of the excel sheet needs to be the column headings
  • Row B onwards of the excel sheet is the data

Excel Exploratory Analysis – provides a summary of key statistics. That includes:

  • Data Summary is a quick diagnostic tool in pandas that gives you a snapshot of the data’s structure, which is invaluable for data cleaning, exploration, and debugging.
  • Number of Nulls is a compact powerhouse for diagnosing missing data allowing you spot trouble areas fast: It shows which columns have missing data, so you don’t have to manually inspect them.
  • Description is a holistic method for summarising the core statistics of your numerical data. It Reveals counts, mean, Standard Deviation, Min / Max, 25%, 50%, 75% percentiles.
  • A heatmap is a vibrant and intuitive way to visualise data using colour to represent values. It’s especially useful when you want to spot patterns, trends, or anomalies across a matrix of numbers.
  • A histogram is a go-to tool for understanding the distribution of numerical data. It’s like taking your entire column of values and asking, “How are these numbers really behaving?”
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Profile Report

  • The overview summary presents the dataset’s size, number of variables, count of missing values, and memory usage.
  • Variable analysis identifies each column’s type—such as numeric or categorical—and provides its distribution, number of unique values, and descriptive statistics.
  • The correlation section calculates relationships between variables
  • Missing values are visualised clearly, showing patterns and percentages across different columns.
  • A sample data preview displays a few rows from the dataset, allowing for quick inspection of its structure and content.
  • The report includes warnings that flag potential issues such as high cardinality, constant columns, or duplicate rows.
  • An interactive HTML output is generated, offering a rich, clickable report that can be saved and shared easily.
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Scatter Plots

A scatter plot is a simple yet powerful chart used to show the relationship between two numerical variables. Each point on the plot represents one observation in your dataset, with its position determined by values on the x-axis and y-axis.


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Line Graphs

Line graphs are powerful visual tools that illustrate trends, patterns, and variations in data over time or across continuous intervals. By connecting individual data points with lines, they create a clear picture of how values evolve—whether rising, falling, or remaining stable—across a defined sequence, such as dates, measurements, or other progressive categories.


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Box Plots

A box plot (also called a box-and-whisker plot) is a compact visual summary of a dataset’s distribution, showing its central tendency, spread, and potential outliers. Here's how it works:


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Pair Plots

A pair plot (also called a scatterplot matrix) is a powerful visual tool used in exploratory data analysis to show relationships between multiple variables in a dataset—all in one grid. It’s especially handy when working with numerical data and trying to spot patterns, correlations, or outliers.


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Linear Regression

Displays all data values and fits a straight line through the points to reveal how data points interact with each other. This includes the formula for the line of best fit and the r value, which indicates the strength and direction of a linear relationship.


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