Visualization Design

Task 1

To determine cryptocurrency price change overtime.For better understanding of prices, it will allow users to check the prices from 2017-2020 data.

The ideal visualization for this task is a line chart. It would be preferable for viewers to review the graph using the line chart because we are presenting patterns in price change from 2017 to 2020. However, we may use the bar chart to demonstrate trends. Bar charts will aggregate the highest and lowest prices for all three cryptocurrencies. Our primary goal is to display data throughout time so that viewers can examine the data point for a specific date in the year and the specific intervals where the price is increasing. Another visualization we might use for this task is a stacked area chart. The main drawback of utilizing stacked area charts here is that there aren't many numerical or categorical variables. When it comes to patterns across time for this task, we only have one numerical variable. Line graphs are preferable for this task since they can project data trends with just one variable.

Visual Encodings

The visual encodings used in this task are text label, position, direction. The Position is used to compute the value by looking at the axis i.e day of date on x axis and closing price on the y axis. Direction shows the fluctuations in the particular coin price, i.e. whether it follows an increasing or decreasing trend. In our visualization, we can see many fluctuations in the data till Jan 20,21 then it started following an increasing trend.In this visualization we have used a filter option for the coin name and date. This is used to help the users get the exact trends of the price for each coin they are looking for.

Cleveland’s rules

Using Cleveland's rules, the most significant information is encoded in position, namely date, followed by the graph's direction. Despite the variations in the graph, we can see that it is on an upward trend.

Gestalt’s principles

In this visualization we have used Gestalt’s principles Law of Continuity from Gestalt’s principles is used in our visualization. Our eyes tend to group things that are aligned with each other. We can see that the line is following in the same direction at some instances for example at Dec 31, at Jan 30 so we tend to see them as a group . Law of similarity from Gestalt’s principle is used in our visualization. We can see that objects with lines in our visualization are perceived as a group.

Visualization design for Task1

Task2

Comparing the average difference between profit/ loss for each coin aggregated over the last month.

For this task, we used a horizontal bar chart. The horizontal chart shows the total number of observations in the data for that particular category. It's used to create quick comparisons between different categories. Another sort of visualization that we can utilize for this task is bubble charts. In our study, we can see in the horizontal bar graph that the value for SHIBA INU is '0,' but the bubble chart does not reveal the category for the zero value because we are just comparing cryptocurrencies for one month. This task can also be accomplished using a line chart. However, identifying the specific numbers at a given position in a line chart is difficult, but a barchart reveals the exact values at a given point. Even if two lines are identical, comparing them in a line chart is challenging, whereas comparing them in a bar chart is straightforward.

Visual Encodings

Position, length, and color are the visual encodings employed in this chart. In our visualization, the visual encoding position is used to determine if the values are positive or negative. The size of the bar is measured using length. For example, we can see that the length of the bar for BNB is -284.3. Color is used to distinguish the coins, with each color representing a different coin. Blue is being used for BNB, orange indicates PancakeSwap, and red represents SHIBA INU.

Cleveland's rule

According to Cleveland's rule, human eyes follow the ranking position. Human eyes tend to see position first in our visualization, which shows positive and negative values. Next, our eyes are drawn to the length of the bar, which indicates how positive and negative the bar is. Finally, the least important information is encoded in color, allowing the coins to be differentiated.

Gestalt’s principles

The Law of Isomorphic correspondence is applicable for this chart. Because when the viewers read the graph it will make it easy for them to understand the difference between the positive and negative values. As per the previous knowledge we learnt in such a way that negative values are on the left side and positive values are on the right side.

Visualization design for Task2

Task3

Analyzing Total number of coins distribution for each coin for last quarter.

We used Histogram to visually illustrate this task. The histogram is used to show the frequency distribution of the total number of coins for the three cryptocurrencies. When there are any gaps in the data, histogram helps to identify them. For example, we discovered gaps between 12B and 13B for SHIBA INU in our visualization, indicating that there is no volume between 12B and 13B. For this task, we may alternatively use a box plot, which also shows the data distribution. But, viewers should have a prior knowledge of quartile ranges, median, and mean in order to understand the distribution of data in a box plot. Our main purpose, however, is to provide the data in such a way that individuals can rapidly understand what is going on with the data. The Histogram will assist them in quickly comprehending the total number of coin distributions for each cryptocurrency. The Bubble chart is another method for visualizing this task. The key problem with the bubble chart is that it aggregates the entire number of coins and projects them as a whole. However, by using the histogram, we can determine which bins have the largest coin distribution, and the histogram will also assist in checking the approximate mean value of a particular cryptocurrency, which cannot be shown in the Bubble chart.

Visual Encodings

Position and length are the visual encodings used in our visualization. The position here is used to determine how the volume of different coins varies. By observing the length of the bar, the visual encoding length may be used to determine how much greater the value is. The highest volume for all coins is between 1B and 3B, as we can see.

Cleveland’s rule

In our visualization, humans are better at discriminating between position and length, according to Cleveland's rule. The most important information here is encoded in position followed by length.

Gestalt’s principles

In our visualization, we use Gestalt's law of similarity. Since all of the bars are the same form (rectangular bars) and color (blue), human eyes view them as a group.In our visualization, we also use Gestalt's Law of Proximity. Because the bars are close together, we see them as a group and make comparisons. For example, we compare which bar has the highest volume and which bar has the lowest volume for BNB and found that 2B has the highest volume and 5B has the lowest volume and compare them with the SHIBA INU.

Visualization design for Task3

Task 4-

What is the proportion of the number of days in which the price of coin increased or decreased from 2017-to 2020?

Pie charts are well suited to tasks that require the estimation of part-to-whole proportions. A stacked area chart is another type of visualization that we can use for this task. The main objective of stacked area charts is to show data for various variables over a period of time; however, because we are aggregating data from 2017 to 2020, a pie chart is preferable than a stacked area chart. We can display the proportions of two segments (i.e. two slices) in a pie chart, which will assist readers in determining the higher and lower rates. However, a stacked bar chart is another alternative option for this task, since it will assist us in determining the proportion of the data.We can use the stacked bar chart instead of the pie chart when there are more segments to show on the graphs. To demonstrate how the stacked bar chart will look for this task, we created a rough drawing, which is given below. A Pie Chart, as compared to a stacked bar chart, shows the proportion of days with higher and lower rates in a more attractive way. Furthermore, a pie chart separates data into pieces by a separation line, allowing users to quickly see which portion of the data has the largest percentage comparing all the three cryptocurrencies.

Rough sketch for the stacked barchart considering the data :-

Visual encodings

The visual encodings used are Length, Angle, Color, Text label. Each slice in the pie chart represents a single component, and the total of all slices equals the entire value. Viewers will eventually be able to compare the percentages of rates as a result of this chart. The reason we use the visual encoding angle is to understand the proportion of days with high and low closing rates. Arc length is used to have a fundamental comprehension of our data to evaluate whether a piece in a pie chart is tiny or huge. We used color to distinguish between grades for low and high rates, with light color indicating low rates and dark color indicating high rates. The text label is used to make it easier to understand the proportional percentages between the low and high rates.

Cleveland’s rule

According to Cleveland's rule, because they are numerical variables in our visualization, our eyes prefer to follow the ranking, and the most essential information is encoded in Arc length, which displays the proportion of the coin. Then our eyes are drawn to the angle, which indicates the value of the slice. Finally, human eyes are drawn to the color, which distinguishes between high and low rates.

Gestalt’s principles

Law of focal point from Gestalt concepts is used in our visualization as distinctive objects serve as a focal point in a visual representation. It stands out from other objects, draws the attention, and encourages users to check further at this point. Because the higher rates differ from the lower rates, our eyes draw attention to a greater proportion which is dark in color.

The Gestalt principles' law of similarity will aid us in identifying all of the higher and lower rates for various cryptocurrencies. We can directly recognize higher rates by dark blue colors and lower rates by light colors using this approach.

Visualization design sketch for Task4

Task5

To represent the correlation between average opening and closing rates of each coin for last year.

To achieve this task we have used Scatter plot. Scatter plot is best suited for this task as it shows the relationship between different attributes. Here in our task Scatter plot shows the relation between open and closing rates for different cryptocurrencies i.e BNB,PancakeSwap, SHIBA INU. The other visualization which we can use for this task is a bubble chart. Using a bubble chart we can also project the relation between the attributes. However, the main drawback with the bubble chart in our task is that our crypto currency has zero relation for the opening and closing rates. In this case the bubble chart will not display any kind of bubble for it. Another main drawback is that bubble chart cannot display the outliers in the data. However, scatter plot can display them. Because from the below chart we can see that. We can also use treemaps for this task, as treemaps are mainly used to define the size of the category with the respective numerical variables. However, it doesn't provide the exact relation between the two numerical variables. In this case by using the scatter plot it provides the relation between the opening and closing rate in such a way that, if you see the plot below where we can see that there is no such point where we have the higher opening rate and closing rate which can be called the difference between them. In such cases scatter plots will help us to analyze the data more than the treemaps do.

Visual Encodings

Position, color, legend, and direction are the visual encodings used in this task. Different colors are used to represent different coin names in this scatter plot. We can easily understand the graph by looking at the legend, where red circles represent the coin SHIBA INU, blue circles represent the coin BNB, and orange circles represent the coin PancakeSwap. We can understand the trend the graph follows by looking at the direction.

Cleveland’s rule

Cleveland’s rule here in the scatter plot follows the ranking of Position and then Color. Our eyes first tend to see the position which is the closing and opening rates of the coins, and then color which differentiates the color for different coins.

Gestalt’s principles

As distinct objects serve as a focal point in a visual representation, the Law of focal point from Gestalt concepts is applied in our visualization. It stands out from other points. The PancakeSwap, which is marked orange in this scatter plot, is the focus point. Our eyes are drawn to the orange color because it contrasts with the majority of the blue circles. Gestalt's law of common fate can be applied to our visualization as well. Lines and shapes that move in the same direction, provide a sense of unity and imply a relationship. They have a common fate. The circles are perceived as a group since they are all moving in the same direction.

Visualization design for Task5