Data Visualization - Intro

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Time Series Visualization

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Time series data A time series is a collection of data points gathered over a period of time and ordered chronologically. The primary characteristic of a time series is that it’s indexed or listed in time order, which is a critical distinction from other types of data sets. If you were to plot the points of time series data on a graph, and one of your axes would always be time. Time series metrics refer to a piece of data that is tracked at an increment in time. For instance, a metric could refer to how much inventory was sold in a store from one day to the next. Time series data is everywhere, since time is a constituent of everything that is observable. As our world gets increasingly instrumented, sensors and systems are constantly emitting a relentless stream of time series data. Such data has numerous applications across various industries. Let’s put this in context through some examples. Examples of time series analysis: Electrical activity in the brain Rainfall measurements Stock...
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Visualizing Associations

Why Visualizing Associations Matters? The human brain is wired to process visuals effectively. Visualizing associations between pieces of information leverages this strength and unlocks a powerful tool for learning and critical thinking. Here's why visualizing associations is important: Pattern Recognition : Our brains excel at finding patterns in visual representations. Charts, graphs, and diagrams allow us to see trends, correlations, and outliers that might be missed in raw data. Imagine a scatter plot revealing a relationship between study hours and exam scores. This visual makes the connection clear. Improved Memory and Recall : Visuals are more engaging and memorable than plain text. By associating information with a visual representation, we strengthen memory pathways and improve recall. Think of a mind map that lays out a complex concept with connecting branches. This is easier to remember than a linear list. Enhanced Communication : Visualizations can bridge communication ...
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Geospatial Mapping

Geospatial Mapping Geospatial mapping is the process of creating visual representations of data that are tied to specific geographic locations. This process helps in understanding patterns, trends, and relationships between data points based on their spatial context.  Here's a step-by-step process for geospatial mapping using a hypothetical example of mapping the population density of different neighborhoods in a city: Data collection and preparation : Gather data related to the variable of interest and its corresponding geographic coordinates. In our example, this would include collecting population data and geographical boundaries for each neighborhood in the city. Ensure the data is accurate, up-to-date, and properly formatted for mapping. Choose a mapping software or tool : Select an appropriate geospatial mapping tool or software, such as ArcGIS, QGIS, or Python libraries like GeoPandas or Folium. The choice depends on factors like complexity, required functionality, and user ...
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