In case making, we often need to show some data, and in order to have a more intuitive effect, we need to use some charts. Ivx has encapsulated some commonly used chart components for us in the expansion component. Today, it is about the application scenarios and use methods of these chart components.
Scatter diagram refers to the distribution diagram of data points on the plane of cartesian coordinate system in regression analysis. Scatter diagram represents the general trend of dependent variables changing with independent variables. Therefore, appropriate functional logarithmic points can be selected for fitting. Typically used to compare aggregated data across categories. The value of its data is an array of objects (as is the case with other icon components), which by default contains five objects, series, X, Y, label, and point size, depending on the nature of the scatter diagram. Each series represents a class of data objects, XY coordinates indicate the position of data points in the coordinate system, labels are used to distinguish each data point in each series, and point size represents the value of each data point, which is calculated according to the unit of XY coordinates. Of course, the size of the closing point can also be set to follow the data.
Radar map is mainly used for the analysis of various attributes of an object, such as enterprise operating conditions — profitability, productivity, liquidity, safety and growth of the evaluation. Its data object array contains series, categories, data, and maximum values. A series is still a distinction between different data objects, and a category is a property that each data object contains. Since the radar chart can be viewed as a percentage, the maximum value needs to be set for each category. (Of course, it works if the value is larger than the maximum value, and a little spike pops up on the chart, but this is something to avoid in specific cases)
In the work, if it is necessary to calculate the proportion of each part of the total cost or amount, it is generally calculated by dividing each part and the total amount. However, this proportion representation method is very abstract. We can use the pie chart to directly display the proportion of each part in a graphical way. The pie chart’s data object array has only three items, series, category, and data. Due to the application environment of the pie chart, we know that a pie chart generally contains only one series, and each item in the category is each component of the series. The total data of each category is the total size of the series, and then the size and proportion of each category can be calculated.
The map chart component is the map of the People’s Republic of China, divided by administrative regions. It can be used to calculate the sales situation of a certain product in different regions, so there is only one item in the general series, and the category is each region. And the value of the data can also be displayed by the color depth level, you can observe more intuitively, compare the value of each region. Of course, you have to set the starting value of the color, the end value and the maximum mapping value, and then the starting value of the color, the end value, and the zero, the maximum mapping value will correspond proportioned.
Gantt charts graphically represent the sequence and duration of a particular item through a list of activities and a time scale. A line diagram with time on the horizontal axis, projects on the vertical axis, and planned and actual completion over time. Visual indication of when to plan, progress versus requirements. Therefore, Gantt charts are often used for project management. The Gantt chart’s data object array is divided into categories, start and end value events. Category corresponds to different items on the Y-axis, and the starting and ending time corresponds to the range of line drawings of this category on the time axis.
Funnel diagram is suitable for the analysis of business processes with relatively standard, long cycle and multiple links. By comparing business data in each link of funnel, problems can be found and explained intuitively. Examples are e-commerce sites, marketing and CRM. In the case of a website, the funnel diagram can show an analysis of certain critical path conversion rates, not only showing the final conversion rate of the user from entering the process to achieving the goal, but also showing the conversion rate of each step along the entire critical path. The series of funnel plots are the same data objects, and the categories represent different critical paths. At the same time, we also found that categories were arranged from top to bottom in the chart from large to small, and the graphic width of each category in the chart was proportional to the data value of the category. For example, we can understand the data in demo that 100 people bought peaches, 80 people bought oranges out of 100 people, 60 people bought bananas out of 80 people bought oranges, 40 people bought apples to 叒 out of 60 people bought apples to buy 20 people bought cantaloupe. (oh! Human nature is indeed a reread machine, and fortunately there is not much data, if there is one more I really do not know contains five more words)
A bar chart consists of a series of vertical bars, usually used to compare the relative sizes of two or more items over a period of time. For example, the comparison of quarterly or annual sales of different products, the allocation of funds to different departments in several projects, the number of types of information each year, etc. Is a more widely used type of chart. The data object array of the bar line chart contains series, categories, and data. The X-axis is divided into categories and series, and the Y-axis represents the size of data values.
Polar coordinate bar graph is a deformation of bar graph in polar coordinate system. And contains two states, the reverse icon closed under the normal state. At this point, we can understand by comparing the bar chart that the X-axis has shrunk to the center of the circle, and the original rectangular bar has also changed into a fan shape. The radius of the fan represents the size of the data, and the largest data value is equal to the radius of the circle.
It can be seen that the most important thing to use the chart component is the relationship between data and chart, that is, the correspondence between data and chart display, and the correspondence between data change and chart display change. The application environment of actual cases is very variable, and there is no universal demo that can meet any scenario. Therefore, in order to make the diagram show the effect we want in actual cases, we must master the logic, and only in this way can we draw inferential conclusions from one example and respond to all changes without changing.