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There are many types of charts. Then how to choose the right chart to achieve the effect of "a picture is worth a thousand words"?
This article divides the charts into several major categories, namely "Comparison class, Proportion class, Trend or correlation class, Distribution class, and others". Users can choose the appropriate chart according to their own purposes.
Introduction: Normal column chart use vertical bars to display numerical comparisons between categories. One axis of the chart shows the category being compared, and the other axis represents the corresponding scale value.
Features: It is not suitable for comparing data with more than 10 categories, and it is recommended to use a bar graph when the classification label is too long.
Examples of scenarios:
Comparison of sales volume of five products.
Introduction: The Contrast Column Chart uses forward and reverse columns to show numerical comparisons between categories. One axis of the chart shows the category being compared, and the other axis represents the corresponding scale value.
Features: It is used to show the comparison of data with opposite meanings. If it is not the opposite meaning, it is recommended to use group column charts.
A comparison of the votes obtained by the "Democrat" and "Republican" in the U.S. general elections in each state.
Introduction: Group column chart is often used to compare different types of data under the same group. Use column height to display numerical comparison, and use color to distinguish different types of data.
Features: Under the same grouping, there can be no too many categories of data.
Examples of scenarios: Compare the monthly sales of drinks, necessities and snacks in the first quarter of 2018. Click to view effect: group column chart.
Introduction: Stacked column chart can compare the total number of groups, and you can also view the size and proportion of each small category contained in each group, so it is very suitable for dealing with the relationship between part and the whole.
Features: Suitable for displaying the total size, but not suitable for comparing the same category under different groups.
Compare the number of visits from Monday to Sunday, and show the number and approximate proportion of users from which channels visit each day.
Introduction: Partitioned line chart is able to separate multiple indicators to reflect the changing trend of things over time or orderly categories.
Features: It is suitable for comparing trends, and can avoid multiple line chart crossing together.
Compare the wind speed trends of the two cities over the same period of time.
Introduction: Radar chart is also called a spidergram. Each of its variables has an axis that emits from the center to the outside. The angles between all the axes are equal, and each axis has the same scale.
Features: Too many variables in the radar chart will reduce the readability of the chart, which is very suitable for displaying performance data.
Compare the performance of two mobile phones on the market. Click to view effect: Line radar chart.
Introduction: Word cloud is an important way to visualize text big data. It is often used to highlight high-frequency sentences and vocabulary in a large amount of text to quickly perceive the most prominent text. It is often used for statistics of high-frequency search fields on websites.
Features: It is not suitable for text data with a large amount of data, nor for data processing with little data distinction.
Use word cloud to display automobile brand. The more sales, the larger the font of the keyword.
Introduction: In the aggregate bubble chart, dimensions define each bubble and measure defines the size and color of bubble.
Features: It is not suitable for data with little distinction.
An aggregate bubble chart is used to show sales volume of different products. Milk that has the largest sales volume has the largest bubble area.
Introduction: The function of the Nightingale rose chart is similar to that of the column chart. It is mainly used for comparison. The value is mapped to the radius of the rose chart.
Features: When the data is relatively similar, it is not suitable to use a pie chart, but a Nightingale rose chart.
The size of the repayment amount is mapped to the arc and radius of each province, and finally a rose diagram is formed.
Introduction: The pie chart generally distinguishes the categories by color, compares the magnitude of the data. It can show the proportion relationship between each category and the whole.
Features: The number of categories cannot be too many, and it is not suitable for data with little distinction.
Introduction: Rectangular tree is suitable for displaying data with hierarchical relationships, and it can intuitively reflect the comparison between the same level. Parent nodes nest child nodes and each node is divided into rectangles of different sizes. The size of the area is used to display the corresponding attributes of the node.
Features: It is very suitable for weighted tree data, comparing the size relationship of each category and the proportion relationship relative to the whole.
Shows the contract amount from 2011 to 2017, with the largest contract amount in 2016. Click to view the effect: Rectangular tree.
Introduction: The percentage stacked column chart compares the proportions of different categories in the same grouped data.
Features: The number of different categories in the same group cannot be too many.
The products produced by the production lines have various grades. The proportion of product grades of each production line is shown in the figure below:
Introduction: Multi-layer pie chart refers to a pie chart with multiple levels and containment relationships between the levels. Multi-layer pie chart is suitable for displaying complex tree structure data with parent-child relationship, such as geographic area data, company upper and lower levels, quarterly, monthly and time levels, etc.
Features: There should not be too many levels and categories, otherwise the slices will be too small and interfere with reading.
The radians of different colors of the inner ring respectively map the sales of each region, and the light color cut of the outer ring represents the sales of different brands in the region.
Introduction: The dashboard sets the target value, which is used to display speed, temperature, progress, completion rate, satisfaction, etc. In many cases it is also used to indicate the proportion.
Features: It is only suitable for data display of a single indicator.
Introduction: The line chart is very convenient to reflect the trend of things changing over time or other ordered categories. 1) It can analyze the interaction and interaction of multiple groups of data over time, so as to summarize and obtain some conclusions and experience. 2) It can compare the size of multiple groups of data at the same time
Features: The number of lines should not be too large, otherwise the readability of the chart will become poor.
Introduction: The range area chart is used to display continuous data, and it can well represent trends, accumulation, reduction, and changes.
Features: It can show the trend of the difference between two continuous variables.
Example scenario:
The following figure shows the change trend of the number of visits and the number of bounces. And the change trend of the difference between the two (non-bounces) is mapped through the change of area.
Introduction: Normal area chart is evolved on the basis of line chart, and it is also convenient to reflect the changing trend of things with time or other ordered categories. Due to the area filling, it can better reflect the trend change than the line chart.
Features: It is better not to exceed five area lines.
Two area lines are used to indicate the "Contract amount" and "Collection amount". It only shows the trend from 2011 to 2017, but also shows the proportion of the collection amount to the contract amount.
Introduction: Scatter chart can display the shape of data clusters and analyze the distribution of data. By observing the distribution of scattered points, the correlation of variables can be inferred, which can be done by data fitting in FineBI.
Features: The scatter chart can better reflect the data distribution when there are more data.
After the scatter chart is completed, the correlation of the data can be analyzed by fitting. As can be seen from the figure below, there is a positive correlation between height and weight, but the correlation is not very strong.
Introduction: The waterfall chart displays the cumulative summary when a value is added or subtracted. It is usually used to analyze the impact of a series of positive and negative values on the initial value (for example, net income).
Features: Through the floating column chart, the increase and decrease of data can be displayed more intuitively.
Introduction : Scatter chart can display the shape of data clusters and analyze the distribution of data. By observing the distribution of scattered points, the correlation of variables can be inferred.
Features : The scatter chart can better reflect the data distribution when there are more data.
For example, using scatter plots and warning lines, it can be seen that most of the men whose height and weight are above average are males.
Introduction: The thermal map displays the weight of each point in the coordinate range in a special highlight way.
Features: The effect is softened, and it is not suitable for accurate data expression. And it is mainly used to see the distribution.
Show the temperature distribution for 24 hours a month.
Introduction: Even if the map component reflects the data on the geographical location, FineBI provides a variety of map components, including thermal map, regional map, flow direction map, point map, etc
Features: Observe data relationships in different areas very intuitively.
Introduction: Funnel chart, also known as inverted triangle chart, has a logical sequence from top to bottom. It is often used for process analysis, such as analyzing which link has abnormal loss rate.
Features: There must be a logical sequence relationship between the upper and lower sides. If there is no logical relationship, it is recommended to use a column chart for comparison.
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