Step 1. Go to the official homepage for Visme and log in using your username and password details. Step 2. Several content options shall be displayed from which you choose the one that suits your needs. These options include Presentations, Infographics, Documents, printables, web graphics, social graphs, and custom graphs.
Simply click Edit in the desired template to proceed. Step 3. Step 4. After that, choose a suitable graph type and enter data within the cells of the subsequent sheet to generate the graph. You have a couple of options like adding data directly or importing them from the external source.
Just click the Import data tab and upload the needed data from the respective source. Step 5. Once you are done, you can then preview the graph and save it. Although the aforementioned list of data visualization tools is great, they never go without weakness. Others have so many disgusting flaws and may become a nightmare owing to the complexity and limited features.
Others are expensive and may drain your financial muscle very much. So, what's the deal. Get yourself Visme and forget all the hurdles you always met before while using other same purpose tools.
Use Visme and take your data visualization to another level. Watch Promo Video. Try Visme Now. Kibana is an open-source data visualization software that was built specifically for the Amazon Elasticsearch engine.
But it can also run in other environments. My main reason for including Kibana on this list of the best open-source data visualization tools in the market currently is its ease of use. The interface is quite intuitive and does not require much technical knowledge to master. It is also relatively easy to create, access, and share visualization dashboards using this tool.
Find Kibana on GitHub here. Just like Kibana, ease of use is my number one reason for recommending KNIME as one of the best open-source data visualization software out there right now. The interface is considerably easy to master.
It also presents its data output in a way that anyone with basic knowledge of charts and graphs can understand.
Find its repository here on GitHub. ColorBrewer is an open-source cartography web application developed by the Pennsylvania State University geography professor Cynthia Brewer. It is in line with her specialty in regard to visibility and color theory in mapping. Although ColorBrewer finds its main use in the visualization of geographical data, it is not limited to this. Instead, it is often employed in data visualization generally.
In any case, my main reason for recommending it is its excellent application in geo-data presentation. Here are some of its features and functionalities that I fell for:. ColorBrewer is distributed on the Apache 2. Its repository is here on GitHub. Leaflet is an open-source JavaScript library with great features for data visualization. I recommend it as one of the best in this sector for the following reasons:. It is one thing to have a list of recommendations as above , but it is a different thing to know the reason behind the recommendations.
If you can have the reasons at your fingertips, then, you can always choose for yourself even if the climate changes for instance, if a once-great tool begins to fall short of the mark. So, what are the points that you should consider in choosing a data visualization tool?
Below, are the points I have for you at the moment:. So, you need to begin the consideration from yourself. Otherwise, you should back out. Every tool has its focus areas. So, ask yourself if a particular tool you are considering would be the one to meet your demands at the moment. For instance, if you are presenting geographical data to elementary school kids, you know it has to be really colorful. So, let this consideration guide your choice of visualization tool. Yes, if you must work with other people in co-viewing data output, then, you need to look beyond just your own expertise level.
If we were to discount the particular needs and preferences that anyone may have, I would pick Google Charts above the rest. Use the Arrow Table tool to create custom arrows for your charts and graphs. Utilize multiple plotters at once There is no limit to the number of plotters you can have open. EZL Features. They can be set to exact locations, or manually placed by dragging them with the mouse. Tab Names — Create custom tab names to intuitively toggle between multiple plotters Curve Identifier Panel — When working with multiple curves, one or more curves may be obscured or difficult to see when its data are plotted beneath other curves.
Images Path Your default images path is the path to which all images will be automatically saved when you click the Image Capture button in the System toolset.
Type This is the image type which will automatically be generated when you click the Image Capture button in the System toolset. Border Color It is often desirable to always use white borders for your image captures.
This is particularly true when you plan to embed your images in presentations or reports where your canvas backgrounds are white. The Border Color control setting can be used for this purpose. Quality Set the quality, and consequently file-size, of the image captures.
Timestamp Image captures are automatically given timestamps within their filenames. This control setting allows you to specify how to format the timestamps. Data Plotting Image. Try For Free. Your default images path is the path to which all images will be automatically saved when you click the Image Capture button in the System toolset.
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