Data Visualization and Analysis Assignment Sample

Introduction of Data Visualization and Analysis Assignment

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Data visualization can be described as the presentation of data in graphical format in order to explore the information of the particular dataset. The elements of the dataset can be envisioned through the bar chart or the box plot. By this visualization, the pattern of the information has been viewed with the proper structures. Various tools can be utilized for the data visualization techniques which can be appropriate for the “Exploratory Data Analysis (EDA)” which can allow the flexible platform in order to identify the pattern of the data as well as the relationship between the several attributes.

Aim and objective

This project aims to visualize the records of the dataset in order to evaluate a particular trend in the information

Objectives

• To implement “interactive data visualization” in the Tableau platform
• To select an appropriate dataset in order to explore the statistical as well as the graphical representation
• To evaluate the relationship between the attributes of the dataset.

Exploration of dataset

This task has been accomplished based on the selected dataset on Diabetes in order to predict the count of the patients based on their medical history. The dataset has been selected from an authenticated site called "Kaggle" in order to estimate the data pattern through visual representation. This dataset consists of 768 rows and 10 columns in order to extract the data of the diabetes victims. The names of the columns are “Serial number, Pregnancies, Glucose, BloodPressure, Skin Thickness, Insulin, BMI, Diabetes Pedigree Function, Age, and Outcome”.

 Diabetes dataset visualization

(Source: Created by the learner)

The above figure has shed light on the glimpse of the dataset into Tableau from the data sources with the values of the dataset.

Research question

Question 1: How many patients have been suffering from blood pressure regarding age?

Question 2: What is the relationship between “BMI and Glucose” intake of the patients?

Question 3: What is the volume of the pregnancies case as well as the thickness of the patients based on the volume of patients?

Question 4: In what range people have been taking insulin?

Question 5: In what range of people has been conceived while suffering from diabetes? 

Design and Implementation

The implementation section has evaluated the answers if the research questions through the graphical presentation of the statistics.

 Barplot age vs blood pressure in Tableau

(Source: Created by the developer)

The above bar plot has represented the range of the age as well as the blood pressure with the appropriate data labels in order to extract the answer to question 1.

 age vs blood pressure in Power BI

The above figure has highlighted the bar chart along with the data labels in the Power BI platform.

 Barplot BMI vs Glucose

(Source: Created by the developer)

The above bar plot has shed light on the representation of the sum of the BMI regarding the quantity of taking glucose in diabetes patients.

 BMI vs Glucose in Power BI

The above figure has illustrated the chart in order to highlight the BMI with respect to Glucose which has been configured in Power BI.

 Box plot of Skin thickness and Pregnancies with respect to the Number of records

(Source: Created by the developer)

The above plot has shed light on the skin thickness of the diabetes patients regarding the total volume of the patients. As illustrated by Figgemeier et al. (2021), it has been stated from the above box plot that the box pilot has provided the representation of the data of the pregnancies cases.

 Pregnancies vs skin thickness in Power BI

The above bar chart has been plotted in the power BI in order to overview the different angle of the pregnancies cases with respect to Skin thickness.

 Barchart age vs insulin in Tableau

(Source: Created by the developer)

The above bar chart has illustrated the volume of the patients who have taken the insulin on a regular basis based on the particular age range.

 Pie chart age vs insulin in Power BI

The above pie chart has elaborated the statistical figure of the insulin intake victim with respect to age in Power BI.

 Blood pressure vs Diabetes pedigree function in Tableau

(Source: Created by the developer)

The above bar chart has showcased that the volume of the "Diabetes Pedigree Function" is 362 based on the aggregation of the blood pressure-volume of the patients.

 Blood pressure vs Diabetes pedigree function in Power BI

The above figure demonstrates the fluctuation of the blood pressure which has been dependable of the diabetes pedigree function.

 Age vs Pregnancies in Tableau

(Source: Created by the developer)

The above figure has highlighted the possible cases of the pregnancies during diabetes as per the age of the patients. It has been depicted that a small number of people have been suffering from diabetes while suffering from diabetes of their age. It has been depicted that the volume of the patients with Diabetes has been retained at the minimum age, and this volume has been increased day by day.

 Age vs Pregnancies in Power BI

Introducing the above figure along with defining the pregnancies cases as per the age in the form of bar chart which has been clearly visualized in the Power BI platform.

 Dashboard in Tableau

(Source: Created by the developer)

Figure 15: Dashboard in Power BI

The above configures have elaborated the visualization of the Dashboard of all graphical representations in Tableau. Based on the concept, it has been illustrated that the dashboard can be described as a collection of the different views in order to make a comparison of the different elements simultaneously. As per the view of DENECKE and NÜSSLI (2020), the creation of the dashboard has been obtained by selecting the sheets in Tableau in order to arrange the views in the horizontal or vertical presentation. This can be stated as the “Design of Prototype” of various views of the data in a structural way in order to explore the relationships between the various attributes at a glance.

Persona

The persona has been implemented based on the research question in order to comprehend the emotion of the reviewers about the diabetes. The respondents have been surprised to see that there have been a lot of people who have been suffering from the diabetes, have belonged to the teenage. Apart from this, the visualization of each graph, the reviewers have structured a comparative analysis regarding the age of blood pressure with respect to glucose intake. By visualizing the dashboard rather said the prototype; the respondents have recognized the statistics of victim at a glance and have gathered a transparent view about the pregnancies cases during the diabetes.

Self reflection

The dataset has been collected from the authenticated site with the utmost effort in order to frame appropriate data visualization in tableau platform. The entire process of the data visualization has provided a great experience along with enriching the knowledge about the prediction as well as plotting in the tableau with the proper categorical dataset. The import of the dataset has been taken a little trouble which has been resolved by loading the dataset with the correct form. All charts have been structured with skillful knowledge by inserting the appropriate attributes of dataset in rows and columns in order to specify measured values.

Cognitive Walkthrough

The term “cognitive walkthrough” can be described as the reusability of the implemented design by the readers. Based on this concept, it has been envisioned that the readers as well as future researchers have flourished with the sound knowledge about the data visualization in the tableau. The incorporation of the aggregate function in the tableau for counting the total victim in each plot has been carried out with ease. The framed dashboard can provide the various perception of the readers with the variance of data simultaneously.

Conclusion

From the above illustration, it has been depicted that the data visualization has been conducted with an ease manner in the platform of Tableau by invoking the various components of the Tableau in different sheets. The labels as well as the filtration of the dataset have been incorporated in order to provide a pictorial view of the information of the diabetic patients. The volume of the pregnant patients and the maximum age range of the patients have been visualized in this analysis. The count of the blood pressure victim patients has been mentioned who have also suffered from diabetes, with the statistical presentation. Moreover, it has been concluded that the bar chart, as well as the box plot of the several elements, has provided the proper visualization of the information. 

References

DENECKE, K. and NÜSSLI, S., 2020. Dashboard visualization of information for emergency medical services. Integrated Citizen Centered Digital Health and Social Care: Citizens as Data Producers and Service co-Creators, 275, p.27.

Figgemeier, H., Henzen, C. and Rümmler, A., 2021. A Geo-Dashboard Concept for the Interactively Linked Visualization of Provenance and Data Quality for Geospatial Datasets. AGILE: GIScience Series, 2, pp.1-8.

Sedrakyan, G., Mannens, E. and Verbert, K., 2019. Guiding the choice of learning dashboard visualizations: Linking dashboard design and data visualization concepts. Journal of Computer Languages, 50, pp.19-38.