Need ideas on how to plot this large set of data

In summary, the conversation discusses the challenge of visualizing data from 450 individual sub-module controllers, with values ranging from 5 to 30,000. The speaker is not well-versed in data visualization and is looking for a way to plot the data in a visually appealing manner without leaving out important information. They consider using a color chart and omitting modules with consistently low values. Other potential ideas include mapping data values to physical locations or grouping modules by software versions.
  • #1
DyslexicHobo
251
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I'm working on monitoring and trending the performance of a memory controller. Without getting into the technical details, I'm trying to find a good way to visualize the data I've collected in a way that will be easy for me to update when I receive new data.

There are about 450 individual sub-module controllers that I'm monitoring about once a month. The value that's being reported each month is a value anywhere from 5 to 30,000 (most are <100, and the ones I'm most interested in visually representing are the ones <100). I have about 200 data points for each of these 450 individual sub-modules, and I just can't figure out how to plot this data in a way that's visually appealing while not leaving out important information.

I'm not really that well-versed in data visualization. I know the basics of Excel but that's about it. I know it's silly to plot all 450 components on one line graph, so I'm hoping there's some plotting method that might apply here.

Let me know if any other info/clarification would help!
 
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  • #2
so you have 450 modules with 200 months worth of data (ie one datapoint per module per month)?

The only thing I can think of is a color chart with x=month and y=module number and each datapoint as a color (blue <100, green >100 to <1000 and say red > 1000 or whatever color scheme you want. Basically you'd have a map of time vs module number horizontal red lines would indicate a module that has consistently had higher values and vertical lines would indicate a group of modules that had higher values for the given month.

Basically if you know what you're wanting to see then design the chart to show it. As an example, maybe you only want to see those modules with high values in the month so just drop the low value ones. Or maybe you want to plot value ranges vs number of modules within the given range.
 
  • #3
This is a great idea! I think I'll use this and just omit all modules with consistently low values.

Thanks for the idea.
 
  • #4
DyslexicHobo said:
This is a great idea! I think I'll use this and just omit all modules with consistently low values.

Thanks for the idea.

Great!

I was also thinking if there are any other features of the modules that could be charted such as location vs recorded data values. As an example, temperature modules being mapped to a physical map showing temperature variations from place to place. Another would be if the modules use different versons of software perhaps grouping them that way to compare software versions vs data values...
 
  • #5


One possible approach to plotting this large set of data would be to use a scatter plot. This would allow you to plot all 450 sub-module controllers on one graph while still being able to see the individual data points. You could also use different colors or shapes to represent different ranges of values, such as <100 or >100, to make it easier to identify trends and patterns. Additionally, you could consider using a trend line or regression analysis to show the overall performance trend of the memory controller. Another option could be to use a heat map, where the color intensity represents the value of the data point, to quickly identify areas of high and low performance. Whatever method you choose, it's important to keep in mind the purpose of the visualization and ensure that it effectively communicates the information you want to convey. It may also be helpful to consult with a data visualization expert or do some research on best practices for visualizing large datasets.
 

1. What is the best way to organize and visualize a large set of data?

The best way to plot a large set of data depends on the type of data and the purpose of the visualization. Some common methods include bar graphs, line graphs, scatter plots, and histograms. It is important to choose a visualization that accurately represents the data and is easy to interpret for the intended audience.

2. How should I choose the appropriate scale for my graph?

Choosing the appropriate scale for your graph also depends on the type of data and the purpose of the visualization. Generally, it is best to use a scale that includes all of the data points and evenly divides the range of data. However, if there are extreme outliers, it may be necessary to adjust the scale to better display the majority of the data.

3. Can I use software to help me plot my data?

Yes, there are many software programs that can help you plot large sets of data. Some popular options include Microsoft Excel, Tableau, and Python's matplotlib library. These programs offer a variety of tools and features to customize and enhance your data visualization.

4. How can I make my data plot more visually appealing?

There are several ways to make your data plot more visually appealing. You can add color, labels, and annotations to make it easier to interpret. You can also experiment with different chart types or use advanced features like data smoothing or animations. It is important to strike a balance between visual appeal and accurately representing the data.

5. Are there any common mistakes to avoid when plotting a large set of data?

Yes, there are a few common mistakes to avoid when plotting data. These include using the wrong type of chart for the data, using a misleading scale, not labeling or titling the graph, and making the graph too cluttered or busy. It is also important to double-check the data for accuracy and to clearly explain the significance of the data in the context of your research or analysis.

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