Data visualisation

Articles tagged Data visualisation

How to visualise data with quirky hand-drawn plots

Charts and plots can often look a bit stale and professional, which might not be appropriate in every setting. If you want to dumb-down your charts and make them look...

How to visualise conversion funnels with Plotly

Funnels are arguably one of the most powerful data visualisations you can use within the ecommerce field. At a glance, they can show you the proportion of customers entering at...

The four Python data science libraries you need to learn

There are hundreds of excellent Python data science libraries and packages that you’ll encounter when working on data science projects. However, there are four of them that you’ll probably use...

How to visualise text data using word clouds in Python

Word clouds (also known as tag clouds, wordles, or weighted lists) have been around since the mid nineties and are one of the most effective data visualisations for representing the...

How to visualise statistical distributions with Seaborn

One of the key steps in the Exploratory Data Analysis process that comes before model development is to understand the statistical distribution of the variables or features within the data...

How to visualise data using Venn diagrams in Matplotlib

The Venn diagram is one of the most intuitive data visualisations for showing the overlap between two or three groups, or “sets”, of data. These diagrams were created in the...

How to visualise data using line charts in Seaborn

Line charts, line graphs, or line plots are among the most widely used data visualisations. They’re ideal for time series data in which you’re plot a metric on the y...

How to visualise data using barplots in Seaborn

Barplots or bar charts are probably the most widely used visualisation for displaying and comparing categorical variables. They’re very easy to understand and are quick and easy to generate.

How to visualise correlations using Pandas and Seaborn

Pearson’s product-moment correlation, or Pearson’s R, is a statistical method commonly used in data science to measure the strength of the linear relationship between variables. If you can identify existing...

How to visualise categorical data in Seaborn

Categorical data can be visualised in many ways, and there’s no requirement to stick to the standard bar chart. Here are a selection of attractive Seaborn charts, graphs, and plots...

How to visualise analytics data using heatmaps in Seaborn

Heatmaps are one of the most intuitive ways to display data across two dimensions, and they work particularly well on temporal data, such as web analytics metrics. They’re a great...

How to visualise RFM data using treemaps

Recent papers on the Recency, Frequency, Monetary (RFM) model, such as this one by Inanc Kabasakal which was published earlier this year, have started to adopt text-based labels to help...

How to visualise data using scatterplots in Seaborn

Scatterplots, scatter graphs, scatter charts, or scattergrams, are one of the most popular mathematical plots and represent one of the best ways to visualise the relationship of data on two...

How to visualise data using histograms in Pandas

During the Exploratory Data Analysis or EDA stage one of the key things you’ll want to do is understand the statistical distribution of your data. Histograms are one of the...

How to visualise data using boxplots in Seaborn

The boxplot, or box-and-whisker diagram, is one of the most useful ways to visualise statistical distributions in data. While they can seem a bit unintuitive when you first look at...