A processing method for data distribution display

Abstract

The present invention relates to the technical field of electric digital data processing, and particularly to a processing method for data distribution display. The method includes: obtaining the quantity Q of target data; obtaining the first target quantity p; initializing the first variable a to 1; if p - a×(c - 1) ≥ a, updating a to c×a and repeating the judgment; otherwise, initializing the second variable b to 1; if a×b < p, updating b to b + 1 and repeating the judgment; otherwise, if (p - min(Q)) / a > 1, establishing a first coordinate system on the user interface to display the distribution of the target data, where the first coordinate system is a coordinate system with the value range of the data as the first horizontal axis and the quantity of the data as the first vertical axis, the number of scales on the first vertical axis is b, and the label of the j-th scale along the extending direction of the first vertical axis on the first vertical axis is a×j. The present invention can solve the problem that the data distribution display is not intuitive and affects the user experience.

Description

Technical Field

[0001] The present invention relates to the technical field of electrical digital data processing, and particularly to a processing method for data distribution display. Background Art

[0002] When displaying data distribution in the prior art, statistics and distribution are often carried out for data sources in a specific field. Since the data distribution of a specific data source is generally regular and the statistical range is relatively limited, a single fixed coordinate system is mostly used for data distribution display. If switching to a new data source and the data range is relatively divergent, the following problems may occur in the drawn data distribution: the gradient between the scales marked on the vertical axis of the coordinate system is relatively large, while the heights of the drawn histograms are all relatively low, that is, the ordinates corresponding to the drawn histograms are all relatively small, which makes it difficult to see the specific values of the vertical axis corresponding to each histogram, resulting in the problem of non-intuitive data distribution display and affecting the user experience. Summary of the Invention

[0003] The purpose of the present invention is to provide a processing method for data distribution display to solve the problem of non-intuitive data distribution display and affecting the user experience.

[0004] According to the present invention, a processing method for data distribution display includes the following steps:

[0005] S100, obtaining the quantity Q of target data, Q = (q1, qz,..., q i ,..., q n ), q i is the quantity of target data located in the ith preset range interval, and the value range of i is from 1 to n, where n is the number of preset ranges.

[0006] S200, obtaining the first target quantity p, p = max(Q), and max() is to take the maximum value.

[0007] S300, initializing the first variable a to 1.

[0008] S400, if p - a×(c - 1) ≥ a, then enter S500; otherwise, enter S600; c is the preset number of scales.

[0009] S500, updating a to c×a, and repeating S400.

[0010] S600, initializing the second variable b to 1.

[0011] S700, if a×b < p, then enter S800; otherwise, enter S900.

[0012] S800, update b to b + 1, and repeat S700.

[0013] S900, if (p - min(Q)) / a > 1, then establish a first coordinate system on the user interface for displaying the distribution of target data. The first coordinate system is a coordinate system with the value range of the data as the first horizontal axis and the quantity of the data as the first vertical axis. The number of scales on the first vertical axis is b, and the label of the j-th scale along the extension direction of the first vertical axis on the first vertical axis is a × j, where the value range of j is from 1 to b; the distance between two adjacent scales on the first vertical axis is Δd, and Δd = d y / b, d y is the length of the vertical axis on the user interface, and min( ) is to take the minimum value.

[0014] The present invention has at least the following beneficial effects:

[0015] For the target data to be displayed with data distribution, the present invention first obtains the maximum value of the data volume corresponding to all preset range intervals, that is, p, and then initializes the first variable a to 1. If the condition p - a × (c - 1) ≥ a is satisfied, then update a to c × a, and repeatedly determine whether the condition p - a × (c - 1) ≥ a is satisfied. If it is not satisfied, then update a to c × a again, and repeatedly determine whether the condition p - a × (c - 1) ≥ a is satisfied, and so on in a loop until the condition p - a × (c - 1) ≥ a is not satisfied; if the condition p - a × (c - 1) ≥ a is not satisfied, then initialize the second variable b to 1. If a × b < p, then update b to b + 1, and repeatedly determine whether a × b < p is satisfied, and so on in a loop until a × b < p is not satisfied; if (p - min(Q)) / a > 1, then determine the number of scales on the vertical axis of the first coordinate system established on the user interface as b, and determine the gradient between two adjacent scales on the corresponding first vertical axis as a. The present invention can adaptively establish a first coordinate system matching the target data. Based on the first coordinate system established by the present invention for displaying data distribution, the quantity of target data in each preset range interval can be fully displayed in the user interface, and the coordinate of the vertical axis corresponding to the preset range interval with the largest quantity of target data in the user interface is relatively close to the maximum value of the labels of the scales displayed on the vertical axis in the user interface, realizing a greater degree of utilization of the user interface, which is beneficial for users to clearly see the specific value of the vertical axis corresponding to each preset range interval, and avoiding the situation that the data distribution display is not intuitive due to the large gradient between the scales marked on the vertical axis for the target data, which affects the user experience. Description of the Drawings

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 A flowchart of a processing method for data distribution display provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0019] According to the present invention, a processing method for data distribution display is provided, such as Figure 1 As shown, the following steps are included:

[0020] S100, obtain the number of target data Q, Q=(q1,q2,…,q i ,…,q n ), q i is the number of target data in the i-th preset range interval, the value range of i is 1 to n, and n is the number of preset ranges.

[0021] In this embodiment, for the target data to be displayed in data distribution, when the target data is to be divided into n categories, the first preset range interval corresponding to the target data is [data min ,data min +(data max -data min ) / n), the second preset range interval corresponding to the target data is [data min +(data max -data min ) / n,data min +2×(data max -data min ) / n), and so on, the n-1th preset range interval corresponding to the target data is [data min +(n-2)×(data max -data min ) / n,data min +(n-1)×(data max-data min ) / n), the nth preset range interval corresponding to the target data is [data min +(n-1)×(data max -data min ) / n,data max ], data min is the minimum value in the target data, data max is the maximum value in the target data.

[0022] S200, obtaining a first target quantity p, where p=max(Q), where max( ) is the maximum value.

[0023] S300: Initialize a first variable a to 1.

[0024] S400, if pa×(c-1)≥a, proceed to S500; otherwise, proceed to S600; c is the preset number of scales.

[0025] Optionally, c is an empirical value, for example, c is 10; preferably, the process of obtaining c includes:

[0026] S010, get the preset initial scale number list num, num=(num1,num2,…,num ε ,…,num ζ ), num ε is the preset εth initial scale number, the value range of ε is 1 to ζ, and ζ is the preset initial scale number.

[0027] Optional, ζ and num ε As a specific implementation, ζ=3, num=(5,10,15).

[0028] S020, traverse num, get num ε The corresponding priority pr ε ,pr ε =sh×qu ε,0 +(1-sh)×(ga ε -p) / ga ε , sh is the preset weight, 0 <sh<1,qu ε,0 For the ε The normalized value, qu ε To num ε When the preset number of scales is determined, the value of b obtained by executing S300-S800 is ga ε To num ε The value of a×b obtained by executing S300 to S800 when the preset number of scales is determined.

[0029] S030, set the maximum priority as num ε and determine it as c.

[0030] Based on c determined by S010 - S030, when displaying the distribution of target data in the established first coordinate system in the case of (p - min(Q)) / a > 1, the difference between the scale with the largest label on the vertical axis and p is relatively small, and the number of displayed scales is relatively large, which is beneficial for users to clearly see the specific values of the vertical axis corresponding to each preset range interval, and avoid the situation that the data distribution display is not intuitive due to the large gradient between the scales marked on the vertical axis for the target data, affecting the user experience.

[0031] S500, update a to c×a, and repeat S400.

[0032] S600, initialize the second variable b as 1.

[0033] S700, if a×b < p, then enter S800; otherwise, enter S900.

[0034] In this embodiment, a in a×b < p is the latest a after executing S300 - S500.

[0035] S800, update b to b + 1, and repeat S700.

[0036] S900, if (p - min(Q)) / a > 1, then establish a first coordinate system on the user interface to display the distribution of target data. The first coordinate system is a coordinate system with the value range of the data as the first horizontal axis and the quantity of the data as the first vertical axis. The number of scales on the first vertical axis is b, and the label of the j - th scale along the extension direction of the first vertical axis on the first vertical axis is a×j, where the value range of j is from 1 to b; the distance between two adjacent scales on the first vertical axis is Δd, and Δd = d y / b, and d y is the length of the vertical axis on the user interface, and min( ) is to take the minimum value.

[0037] In this embodiment, a in S900 is the latest a after executing S300 - S500, and b in S900 is the latest b after executing S600 - S800.

[0038] In this embodiment, for the target data to be displayed in terms of data distribution, first obtain the maximum value of the data volume corresponding to all preset range intervals, that is, p. Then initialize the first variable a to 1. If the condition p - a×(c - 1) ≥ a is satisfied, update a to c×a, and repeatedly determine whether the condition p - a×(c - 1) ≥ a is satisfied. If it is not satisfied, then update a to c×a again, and repeatedly determine whether the condition p - a×(c - 1) ≥ a is satisfied, and so on in a loop until the condition p - a×(c - 1) ≥ a is not satisfied. If the condition p - a×(c - 1) ≥ a is not satisfied, then initialize the second variable b to 1. If a×b < p, update b to b + 1, and repeatedly determine whether a×b < p is satisfied, and so on in a loop until a×b < p is not satisfied. If (p - min(Q)) / a > 1, determine the number of scales on the vertical axis of the first coordinate system established on the user interface as b, and determine the gradient between two adjacent scales on the corresponding first vertical axis as a. This embodiment can adaptively establish a first coordinate system that matches the target data. Based on the first coordinate system established in this embodiment for displaying data distribution, the number of target data in each preset range interval can be fully displayed in the user interface, and the coordinate of the vertical axis corresponding to the preset range interval with the largest number of target data in the user interface is relatively close to the maximum value of the scale labels displayed on the vertical axis in the user interface, achieving a greater degree of utilization of the user interface, which is beneficial for the user to clearly see the specific value of the vertical axis corresponding to each preset range interval, and avoiding the situation that the data distribution display is not intuitive due to the relatively large gradient between the scales marked on the vertical axis for the target data, which affects the user experience.

[0039] As a preferred specific implementation manner, S900 further includes: if (p - min(Q)) / a ≤ 1, (floor(min(Q) / a) + 1)×a ≥ p and a ≠ 1, establish a second coordinate system on the user interface to display the distribution of the target data. The second coordinate system is a coordinate system with the value range of the data as the second horizontal axis and the quantity of the data as the second vertical axis. The number of scales on the second vertical axis is c + 1, and the label of the v-th scale on the second vertical axis along the extending direction of the second vertical axis is floor(min(Q) / a)×a + (v - 1)×a / c, where the value range of v is from 1 to c + 1, and floor( ) is the floor function.

[0040] Based on the second coordinate system established according to the above preferred specific implementation manner, when (p - min(Q)) / a ≤ 1, (floor(min(Q) / a) + 1)×a ≥ p and a ≠ 1, the labels of the scales within the range of floor(min(Q) / a)×a to (floor(min(Q) / a) + 1)×a can be displayed on the vertical axis with a gradient of a / c. Since each q in Q iIt is within the range of floor(min(Q) / a)×a to (floor(min(Q) / a)+1)×a, which is conducive to users clearly seeing the specific values of the vertical axis corresponding to each preset range interval; preferably, the second coordinate system no longer displays the scale labels in other ranges except from floor(min(Q) / a)×a to (floor(min(Q) / a)+1)×a, which is conducive to increasing the distance between adjacent scales on the user interface, conducive to users clearly seeing the specific values of the vertical axis corresponding to each preset range interval, and avoiding the situation that the data distribution display is not intuitive due to the relatively large gradient between the scales marked on the vertical axis for the target data, affecting the user experience.

[0041] As a preferred specific implementation manner, S900 further includes: if (p - min(Q)) / a ≤ 1, (floor(min(Q) / a)+1)×a < p and a ≠ 1, then a third coordinate system is established on the user interface to display the distribution of the target data. The third coordinate system is a coordinate system with the value range of the data as the third horizontal axis and the quantity of the data as the third vertical axis. The number of scales on the third vertical axis is δ, and δ = (ceil(p / (a / c)) - floor(min(Q) / (a / c))) / (a / c) + 1. The label of the w-th scale along the extending direction of the third vertical axis on the third vertical axis is floor(min(Q) / (a / c))×a / c + (w - 1)×a / c, and the value range of w is from 1 to δ.

[0042] Based on the above preferred specific implementation manner, when (p - min(Q)) / a ≤ 1, (floor(min(Q) / a)+1)×a < p and a ≠ 1, the scale labels within the range of floor(min(Q) / (a / c))×a / c to ceil(p / (a / c)×a / c are displayed on the vertical axis with a gradient of a / c. Since each q in Q i It is within the range of floor(min(Q) / (a / c))×a / c to ceil(p / (a / c)×a / c, which is conducive to users clearly seeing the specific values of the vertical axis corresponding to each preset range interval; moreover, preferably, the second coordinate system no longer displays the scale labels in other ranges except from floor(min(Q) / (a / c))×a / c to ceil(p / (a / c)×a / c, which is conducive to increasing the distance between adjacent scales on the user interface, conducive to users clearly seeing the specific values of the vertical axis corresponding to each preset range interval, and avoiding the situation that the data distribution display is not intuitive due to the relatively large gradient between the scales marked on the vertical axis for the target data, affecting the user experience.

[0043] In this embodiment, for other cases except (p - min(Q)) / a > 1, (p - min(Q)) / a ≤ 1, (floor(min(Q) / a) + 1)×a ≥ p and a ≠ 1, and (p - min(Q)) / a ≤ 1, (floor(min(Q) / a) + 1)×a < p and a ≠ 1, a fourth coordinate system is established on the user interface to display the distribution of target data. The fourth coordinate system is a coordinate system with the value range of the data as the fourth horizontal axis and the quantity of the data as the fourth vertical axis. The number of scales on the fourth vertical axis is b, and the label of the j-th scale along the extension direction of the fourth vertical axis is a×j, where the value range of j is from 1 to b; the distance between two adjacent scales on the fourth vertical axis is Δd, and Δd = d y / b, d y is the length of the vertical axis on the user interface, and min( ) is to take the minimum value.

[0044] In this embodiment, when displaying the distribution of target data, n rectangular bars are used to represent the distribution of target data in n preset range intervals. The widths of different rectangular bars in the horizontal axis direction are equal, and the height of the i-th rectangular bar in the vertical axis direction is positively correlated with q i correlated.

[0045] In this embodiment, the interval of the horizontal axis corresponding to the i-th rectangular bar is [data min +(i - 1)×(data max - data min ) / n, data min + i×(data max - data min ) / n), and the value of the vertical axis corresponding to the i-th rectangular bar is q i .

[0046] As a specific implementation, p = 421, min(Q) = 80, c = 10, a = 100, b = 5. A first coordinate system is established. The gradient between the scales on the first vertical axis is 100. The number of scales on the first vertical axis of the first coordinate system is 5. The label of the 1st scale along the extension direction of the first vertical axis is 100, the label of the 2nd scale along the extension direction of the first vertical axis is 200, the label of the 3rd scale along the extension direction of the first vertical axis is 300, the label of the 4th scale along the extension direction of the first vertical axis is 400, and the label of the 5th scale along the extension direction of the first vertical axis is 500.

[0047] As a preferred specific implementation, when displaying the distribution of target data, the i-th rectangular bar is displayed in the target color corresponding to the i-th preset range interval. The process of obtaining the target color corresponding to the i-th preset range interval includes:

[0048] S910, obtaining the color coefficient k corresponding to the i-th preset range interval i , k i =|q i -mean(Q)| / (max(E)), E is the difference sequence of the data to be displayed, E=(|q1-mean(Q)|,|q2-mean(Q)|,…,|q i -mean(Q)|,…,|q n -mean(Q)|), mean( ) is the average value.

[0049] S920, matching is performed in a preset color relationship table G, G=(g1, g2, ..., g z ,…,g m ), g z is the zth color relation in G, g z =(gu z ,gr z ), gu z g z The corresponding color coefficient, gr z g z The corresponding color, z ranges from 1 to m, where m is the number of color relationships in G.

[0050] In this embodiment, G is a pre-established table. Preferably, when gu z =0, gr z Green; when z =0.5, gr z Yellow; when z =1, gr z is red; thus, in the user interface, the histogram whose corresponding target data quantity is mean(Q) is displayed in green, the histogram whose corresponding target data quantity has a moderate difference with mean(Q) is displayed in yellow, and the histogram whose corresponding target data quantity has the largest difference with mean(Q) is displayed in red, which helps users quickly identify the histograms in the user interface that have no difference with mean(Q), have a moderate difference with mean(Q), or have the largest difference with mean(Q).

[0051] Preferably, when gu z In the range of 0-0.5, as gu z The increase of gr z The color changes from green to yellow; when z In the range of 0.5-1, as gu z The increase of gr zThe color of the square changes from yellow to red. Therefore, the user can infer the difference between the number of target data corresponding to each square and mean(Q) based on the color of each square on the user interface.

[0052] In this embodiment, G and k i The matching color relationship is that the corresponding color coefficient in G is k i Optionally, S920 includes:

[0053] S921, initialize the third variable f to 1.

[0054] S922, if g f The corresponding color coefficient gu f Equal to k i , then go to S923; otherwise, go to S924.

[0055] S923, will g f Determined to be in G and k i Matching color relationships.

[0056] S924, update f to f+1, and repeat S922.

[0057] Based on S921-S924, it is possible to obtain the G and k i Matching color relationships.

[0058] S930, replace G with k i The color corresponding to the matched color relationship is determined as the target color corresponding to the i-th preset range interval.

[0059] Based on S910-S930, the color of the histograms corresponding to the preset range intervals with the same magnitude of difference from mean(Q) in the user interface is the same, which helps users quickly understand the preset range intervals with the same magnitude of difference from mean(Q). As a preferred embodiment, a heat map representing the correspondence between color coefficients and colors is displayed at a preset position in the user interface. The heat map is in the form of long strips extending along the vertical axis. As a result, users can quickly understand the magnitude of the difference between the quantity corresponding to each histogram in the user interface and mean(Q) based on the color of each histogram and the heat map.

[0060] Although some specific embodiments of the present invention have been described in detail by way of example, it should be understood by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present invention. It should also be understood by those skilled in the art that various modifications may be made to the embodiments without departing from the scope and spirit of the present invention. The scope of the present invention is defined by the appended claims.

Claims

1. A processing method for data distribution display, characterized in that: It includes the following steps: S100, obtain the number of target data Q, Q=(q1,q2,…,q i ,…,q n ), q i is the number of target data in the i-th preset range interval, i ranges from 1 to n, and n is the number of preset ranges; S200. Obtain the first target quantity p, where p = max(Q), and max( ) is to take the maximum value; S300. Initialize the first variable a to 1; S400. If p - a×(c - 1) ≥ a, then enter S500; otherwise, enter S600; c is the preset number of scales; S500. Update a to c×a, and repeat S400; S600. Initialize the second variable b to 1; S700. If a×b < p, then enter S800; Otherwise, enter S900; S800. Update b to b + 1, and repeat S700; S900, if (p-min(Q)) / a>1, then establish a first coordinate system on the user interface to display the distribution of the target data, the first coordinate system is a coordinate system with the value range of the data as the first horizontal axis and the number of data as the first vertical axis, the number of scales on the first vertical axis is b, the label of the jth scale along the extension direction of the first vertical axis on the first vertical axis is a×j, and the value range of j is 1 to b; the distance between two adjacent scales on the first vertical axis is Δd, Δd=d y / b,d y is the length of the vertical axis on the user interface, and min() is the minimum value.

2. The processing method for data distribution display according to claim 1, characterized in that: S900 further includes: If (p - min(Q)) / a ≤ 1, (floor(min(Q) / a) + 1)×a ≥ p, and a ≠ 1, then establish a second coordinate system on the user interface to display the distribution of target data. The second coordinate system is a coordinate system with the value range of the data as the second horizontal axis and the quantity of the data as the second vertical axis. The number of scales on the second vertical axis is c + 1, and the label of the v-th scale along the extension direction of the second vertical axis on the second vertical axis is floor(min(Q) / a)×a + (v - 1)×a / c, where the value range of v is from 1 to c + 1, and floor( ) is to round down.

3. The processing method for data distribution display according to claim 1 or 2, characterized in that: When displaying the distribution of target data, n histograms are used to represent the distribution of target data in n preset ranges. The widths of different histograms along the horizontal axis are equal, and the height of the i-th histogram along the vertical axis is equal to q. i Positive correlation.

4. The processing method for data distribution display according to claim 3, characterized in that: When displaying the distribution of target data, display the i-th rectangular block with the target color corresponding to the i-th preset range interval. The process of obtaining the target color corresponding to the i-th preset range interval includes: S910, obtaining the color coefficient k corresponding to the i-th preset range interval i , k i =|q i -mean(Q)| / (max(E)), E is the difference sequence of the data to be displayed, E=(|q1-mean(Q)|,|q2-mean(Q)|,…,|q i -mean(Q)|,…,|q n -mean(Q)|), mean( ) is the average value; S920, matching is performed in a preset color relationship table G, G=(g1, g2, ..., g z ,…,g m ), g z is the zth color relation in G, g z =(gu z ,gr z ), gu z g z The corresponding color coefficient, gr z g z The corresponding color, z ranges from 1 to m, where m is the number of color relations in G; S930, replace G with k i The color corresponding to the matched color relationship is determined as the target color corresponding to the i-th preset range interval.

5. The processing method for data distribution display according to claim 4, characterized in that: S920 includes: S921. Initialize the third variable f to 1; S922, if g f The corresponding color coefficient gu f Equal to k i , then go to S923; otherwise, go to S924; S923, will g f Determined to be in G and k i Matching color relationships; S924. Update f to f + 1, and repeat S922.

6. The processing method for data distribution display according to claim 1, characterized in that: c=10。 7. The processing method for data distribution display according to claim 1, characterized in that: S900 further includes: If (p - min(Q)) / a ≤ 1, (floor(min(Q) / a) + 1)×a < p, and a ≠ 1, then establish a third coordinate system on the user interface to display the distribution of target data. The third coordinate system is a coordinate system with the value range of the data as the third horizontal axis and the quantity of the data as the third vertical axis. The number of scales on the third vertical axis is δ, where δ = (ceil(p / (a / c)) - floor(min(Q) / (a / c))) / (a / c) + 1, and the label of the w-th scale along the extension direction of the third vertical axis on the third vertical axis is floor(min(Q) / (a / c))×a / c + (w - 1)×a / c, where the value range of w is from 1 to δ.

8. The processing method for data distribution display according to claim 4, characterized in that: Display a heat map for representing the correspondence between color coefficients and colors at a preset position on the user interface.

9. The processing method for data distribution display according to claim 8, characterized in that: The heat map is in a long strip shape along the extension direction of the vertical axis.

10. The processing method for data distribution display according to claim 4, characterized in that: Danggu z =0, gr z Green; when z =0.5, gr z Yellow; when z =1, gr z It is red.

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