1, data wrapper
Datawrapper is an online data visualization tool for making interactive charts. Once you upload data from a CSV file or paste it directly into a field, Datawrapper will generate a bar, line or any other related visual file. Many journalists and news organizations use Datawrapper to embed real-time charts in their articles. It is very easy to use and generate effective graphics.
2. The form is open
TableauPublic is probably the most popular visualization tool, which supports various graphs such as charts, graphs and maps. This is a completely free tool, and charts made with it can be easily embedded in any web page. They have a good gallery to show the visualization created by Tableau.
Although the charts and graphs it provides are much better than other similar tools, I don't like to use its free version because it has a big footer. If it's not as big as mine, you must try it. Or you can go to the paid version if you can afford it.
3. Smartphones
As a mature big data analysis platform, Smartbi has a unique display effect of reusability and dynamic and static combination, which makes data visualization flexible and powerful, suitable for both dynamic and static, and provides users with unlimited application ability and imagination space.
In addition to supporting the use of Excel as a report designer, it is also perfectly compatible with Excel configuration items. Support all the complicated dashboard styles such as Excel's built-in graphics, background images and conditional formats, as well as the complete ECharts graphics library, and support dozens of dynamic interactive graphics, including waterfall charts, relationship charts, radar charts, oil quantity charts, heat charts and tree charts. With the help of geographic information technology, it also created a map analysis function.
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Very suitable for small projects. Although there are only six chart types, the open source library is the perfect data visualization tool for hobbies and small projects. Drawing charts and creating responsive graphic designs using HTML5canvas elements is rapidly becoming one of the most popular open source chart libraries.
5. Raw
Raw defines itself as "the missing link between spreadsheet and vector graphics". It is based on and carefully designed. It has such an intuitive interface that you will feel that you have used it before. It is open source and does not require any registration.
It has a library of 2 1 chart type to choose from, and all the processing is done in the browser. So your data is safe. RAW is highly customizable and extensible, and can even accept new customized layouts.
6. Infographic
Infogram enables you to create charts and graphs online. It has a limited free version and two payment options, including 200+ maps, private enjoyment and logo library.
It is equipped with an easy-to-use interface and its basic charts are well designed. One feature I don't like is that when you try to embed interactive charts into a web page (free version), you will see a huge logo. If they can be as good as the small text used by DataWrapper.
7. Timeline
As the name implies, TimelineJS can help you create a beautiful timeline without writing any code. It is a free open source tool and is used by some of the most popular websites, such as Time and Radiolab.
This is a very simple four-step process to create your schedule, which is explained here. The best part? It can get media from various sources and has built-in support for Twitter, Flickr, Google Maps, YouTube, Vimeo, Vine, Daily Motion, Wikipedia, SoundCloud and other similar websites.
8. conspiratorially
Plotly is a data analysis and drawing tool based on Web. It supports a good collection of chart types with built-in social sharing function. Available charts and chart types have a professional look and feel. To create a chart, you only need to load information and customize the layout, axis, notes and legend. If you want to start, you can find some inspiration here.
9. Visualization is free
VisualizeFree is a hosting tool that allows you to use publicly available datasets, or upload your own datasets and build interactive visualizations to demonstrate data. Visualization is far more than a simple chart, the service is completely free, and the development work needs Flash, and the output can be completed through HTML5.
Origin software The function of origin drawing software is downloaded for free.
Link:
Extraction code: 9tmr
Origin platform was officially released by ElectronicArtsInc (EA) on 20 1 1. EA invested heavily to build an all-round game social platform, and its Mac version began public beta at the end of 20 12.
How to analyze data with spss? After entering the data, you can start with the basic data statistics-descriptive statistics. Then according to your data results, see if you need correlation regression or other analysis. Descriptive statistics in spss are mainly analytical-descriptive, including descriptive statistics, frequency statistics and cross analysis. Descriptive statistical analysis is the first step of statistical analysis. First, select analyze, and you will see descriptive. Then, use the mouse to select descriptive menu. The four most commonly used processes are listed above: the frequency process is characterized by generating frequency tables; Descriptive process for general statistical description; When the data profile is unclear, the exploration process is used for exploratory analysis; The crosstab process completes the statistical description and general statistical test of count data and grade data. Select Analysis first, then Descriptive to open any analysis window. After selecting the data to be analyzed, you can press the left mouse button to select and middle mouse button to splice them together, and then click the pop-up statistics dialog box to define other descriptive statistics to be calculated. Mean, median, mode, sum and so on can be analyzed. Then you can click on the chart dialog box and select histogram, pie chart, etc. Painting. When you are sure, click the Continue button and select OK. Do it. There will be output results directly. You can look at the results of descriptive statistics first to see if there are missing values or untrue data. If so, the data need to be revised and analyzed by descriptive statistics. I think it's quite detailed. Hehe ~ ~ ~ ~