Graded Assignment -3 (May Term 2023):- Effective Visualization of Data #14
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Sayan Rakshit Brief InformationAntibiotics are substances that can kill or inhibit the growth of bacteria. They are used to treat bacterial infections and are one of the most important tools in modern medicine. However, not all antibiotics work against all bacteria. The effectiveness of an antibiotic depends on the type of bacteria it is being used against. The Minimum Inhibitory Concentration (MIC) is a measure of how effective an antibiotic is against a particular type of bacteria. It is the lowest concentration of the antibiotic that can prevent the growth of the bacteria. The lower the MIC, the more effective the antibiotic is against that type of bacteria. Bacteria can be classified as either gram-positive or gram-negative based on the structure of their cell walls. Gram-positive bacteria have thick cell walls made up of a substance called peptidoglycan. When subjected to a laboratory test called a Gram stain, these bacteria retain a purple dye and appear purple under a microscope. Gram-negative bacteria, on the other hand, have thinner cell walls and an additional outer membrane. They do not retain the purple dye during a Gram stain and appear pink or red under a microscope. Aim of the Visualization
Design Decision
Scale, Visual Encoding and Color
Noteworthy observations
Tool/s UsedThe entire visualization was made using Tableau Public |
Comparing Effectiveness of Antibiotics using Minimum Inhibitory Concentration [MIC]Anant Kumar
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Visualizing Effectiveness of several Antibiotics using Minimum Inhibitory Concentration (MIC)Name: Prahlad Singhania Introduction: Objectives of Visualization: Design Decision: Visual Encodings: Key findings: Visualization:
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Communicating the Effectiveness of Antibiotics on Bacterial InfectionsName: Sejal Anand 
PurposeMy objective was to create a visualization that effectively communicates the performance of three popular antibiotics (Penicillin, Streptomycin, and Neomycin) on 16 different bacteria. The dataset contains minimum inhibitory concentration (MIC) values, representing the effectiveness of each antibiotic against specific bacterial infections. To achieve this, I designed a scatterplot using Tableau, where each bacteria is represented as a data point, and the MIC values of the three antibiotics are displayed on the respective axes. The color and shape of the data points were used to indicate the type of antibiotic and the Gram staining of each bacteria, respectively. Additionally, I included a table with color-coded bacteria rows to further support quick interpretation. Design Decision and RationaleI chose a scatterplot as it is suitable for comparing multiple data points across different categories. Each bacteria is represented as a data point to show its response to different antibiotics. Using log transformation on the MIC values ensures that data with a wide range of concentrations can be visualized effectively on the same chart, preventing large differences in values from dominating the visualization. Visual Encodings, Scale and ColorI used position encoding for the data points, placing them on the chart according to their MIC values for each antibiotic. This allows viewers to compare the effectiveness of different antibiotics on the same bacteria easily. Additionally, colour encoding was applied to represent the three antibiotics, making it effortless to identify them. Shape encoding was employed to differentiate between Gram-positive and Gram-negative bacteria, further enhancing the clarity of the visualization. Using log transformation on the MIC values ensures that the data is appropriately scaled on the chart, allowing viewers to perceive differences accurately. This transformation also prevents extreme values from skewing the visualization and enables the visualization of a wide range of concentrations on the same chart. ShortcomingsWhile the scatterplot effectively communicates the relative effectiveness of antibiotics on different bacteria, it may not show the full extent of the variations in MIC values. Extreme outliers may not be as apparent due to the log transformation, potentially downplaying their significance. Additionally, if there are overlapping data points, it could be challenging to distinguish individual data points accurately. In such cases, using interaction techniques or tooltips in Tableau could help reveal specific data points. Tool used |
https://public.tableau.com/app/profile/dhruv1897/viz/AntibioticPerformance/Sheet1?publish=yes DHRUV SANAN DescriptionThe use of a bar chart makes it easy to see at a glance which antibiotics are most effective against each type of bacteria. The lower the bar, the lower the MIC, which means that less of the antibiotic is needed to kill the bacteria. Critic of my visualisationSome aspects of the data that might be obscured or downplayed due to the visualization design include the following: Here are some suggestions for how to improve the chart:Add a table below the chart that shows the exact MIC values for each antibiotic and bacteria. OverviewOverall, the chart created is an effective way to communicate the data on antibiotic susceptibility. The use of a heatmap, different colors, and a clear title and axis labels make the data easy to understand. The logarithmic scale of the y-axis helps to highlight the differences in MIC between the antibiotics. |
Minimum inhibitory concentration Visualisation
IntroductionBacteria, microscopic single-celled organisms, play a significant role in both beneficial and harmful interactions within our environment. In the medical field, understanding bacterial behaviour and identifying their susceptibility to antibiotics are essential for effectively combating infections. Two crucial aspects that aid in this understanding are Minimum Inhibitory Concentration (MIC) and Gram staining. Minimum Inhibitory Concentration (MIC):The Minimum Inhibitory Concentration (MIC) is a measure of the effectiveness of antibiotics against specific bacterial strains. It represents the lowest concentration of an antimicrobial agent (such as an antibiotic) required to prevent visible growth of the bacteria in a controlled laboratory environment (in vitro). Determining the MIC value helps clinicians gauge the potency of an antibiotic against a particular bacterial infection. Lower MIC values indicate that the antibiotic is highly effective in inhibiting bacterial growth at lower concentrations, while higher MIC values may indicate reduced effectiveness and the need for higher antibiotic concentrations to achieve the desired effect. Gram Staining:Gram staining is a fundamental microbiological technique used to categorise bacteria into two main groups: Gram-positive and Gram-negative. This staining method is based on differences in the bacterial cell wall structure. Bacteria that retain the stain, appearing purple or dark blue, are classified as Gram-positive. Conversely, bacteria that do not retain the stain, appearing pink or red, are categorised as Gram-negative. This classification is important in determining appropriate antibiotics for treatment, as Gram-positive and Gram-negative bacteria may exhibit varying levels of susceptibility to different antimicrobial agents. ObjectivesThe primary goal of this visualisation is to compare the minimum inhibitory concentration (MIC) of each antibiotic for different bacterial infections and to identify patterns and differences in their effectiveness. The secondary goal is to explore how the reaction to Gram staining (Gram-positive or Gram-negative) might influence antibiotic effectiveness. Design DecisionTo achieve the goals, i decided to go with a interactive bubble chart. Apart from interactive visualisation, i tried to get a tabular form visualisation that is considered to be main visualisation for this graded activity. link: https://public.flourish.studio/visualisation/14522699/ Data Comparison and Exploration:The interactive bubble chart table allows viewers to compare the MIC values of multiple antibiotics for each bacterial infection side by side. This aids in identifying patterns, differences, and similarities in antibiotic effectiveness across different bacteria. The interactive nature enables users to explore the data by hovering over the bubbles for detailed MIC values, supporting a deeper understanding of antibiotic efficacy for specific infections. Intuitive Representation:Bubbles are a familiar and intuitive way to represent quantitative data, with the size of each bubble proportional to the MIC value. This visual encoding makes it easy for viewers to grasp the relative potency of antibiotics for each bacterial infection. Organization and Clarity:The table format ensures a structured and organised presentation of the data, with each bacterial infection having its dedicated row. This format minimises clutter and allows viewers to focus on individual bacteria and their corresponding antibiotic responses. By maintaining consistency across all bacterial infections, viewers can quickly comprehend the layout and navigate through the information efficiently. Aesthetics and Engagement:The choice of light green and light red backgrounds complements the bubble chart and creates an aesthetically pleasing and visually harmonious presentation. The interactive nature and color-coding encourage viewer engagement, fostering curiosity and interest in exploring the data further. Consistency:Standardising the visualisation format across different bacteria ensures consistency and ease of navigation for viewers. They can focus on interpreting the data without having to adapt to different visualisation styles for each bacteria. Visualisation
Visual EncodingsIn data visualisation, visual encodings are essential in effectively conveying information through visual representations. Carefully chosen colour semantics play a crucial role, as they can represent various motives, such as positive or negative trends. Additionally, the background colour is thoughtfully selected to ensure it complements the colors of the interactive bubbles, providing a harmonious and visually pleasing experience. To enhance clarity and ease of interpretation, the bacteria are presented in alphabetically sorted order. This deliberate arrangement allows viewers to quickly locate specific bacterial infections and makes it simpler to compare antibiotic responses across different bacteria. To aid viewers in understanding the visual encoding and its significance, appropriate legends are thoughtfully included. These legends provide clear explanations of color representations, bacterial names, and antibiotic MIC values. With the support of these legends, viewers can easily interpret the interactive bubble chart and gain valuable insights into antibiotic effectiveness for various bacterial infections. shortcomings and Improvements:
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Name:Deepanshu Mahajan Title: Effectiveness of Antibiotics on Bacterial Infections - Minimum Inhibitory Concentration (MIC) Heatmap Visualization Type: Heatmap Rationale: Visual Encodings: Color: The color encoding accurately represents the MIC values, allowing viewers to distinguish between bacteria with different levels of antibiotic resistance. The warm colors draw attention to higher MIC values, indicating potential challenges in treating bacterial infections, while cooler colors highlight effective antibiotics. Design Decisions: Sorting: I have not sorted the bacteria or antibiotics to maintain their original order in the dataset. This decision ensures that the heatmap presents the data as gathered, making it easier for viewers to refer back to the original dataset if needed. Gram Staining: To handle the qualitative data on Gram staining (positive/negative), I transformed it into numerical values. Bacteria with positive Gram staining are represented with '1', and bacteria with negative Gram staining are represented with '0'. This transformation enables the inclusion of Gram staining information in the heatmap. Limitations: |
Antibiotic Performance Visualization for 16 Bacterial InfectionsName: Savindra Singh Shekhawat
PurposeThe primary goal of this visualization was to effectively present the performance of three widely used antibiotics (Penicillin, Streptomycin, and Neomycin) against 16 different bacterial infections. The dataset consists of minimum inhibitory concentration (MIC) values, indicating the efficacy of each antibiotic against specific bacteria. To achieve this, I developed a visualization using R, where each bacteria is depicted as a slice on the chart. Within each slice, the MIC values of the three antibiotics are displayed. The color and shape of the data points were utilized to signify the type of antibiotic and the Gram staining of each bacteria, respectively. Design ChoiceI opted for this particular plot as it allows for easy comparison of multiple data points across distinct categories. By representing each bacterium as a data point, we can observe its response to different antibiotics effectively. Additionally, the size of the bars provides insight into the effectiveness of each drug. Visual Encodings, Scale and ColorIn this visualization, the following color scheme was utilized to represent the antibiotics: Penicillin: Blue Additionally, the background colors for the bacterial groups were chosen as follows: Gram-Positive Bacteria: Light Purple/Lavender ShortcomingsWhile this visualization conveys information effectively, one potential shortcoming could be the potential misinterpretation of the quantity required, as the size of bars is used for representation. Apart from that, the visualization serves its purpose well in presenting the antibiotic performance data for various bacterial infections. |
Comparing Effectiveness of 3 Famous Drugs Against EachotherVarun Sood (21F1003382)
Brief Information:--> The MIC:
-> The Gram-Staining:
Visualization Goals:-
Designing Logic Used:-
Drawable Observations:-
The Bottom Line Verdict:-
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Logarithmic bar chart visualization for comparison of the performance of various antibiotics on bacteria.Name: Andiboyina Mourya Chakradhar Nagesh Note: Due to the size of the chart, it is recommended to open the image in a new tab. Introduction:Single-celled organisms like bacteria are known to be some of the deadliest organisms known to mankind. While some of the species of bacteria play a vital role in our human body, bacteria that enter the human body through external means and cause diseases are considered a threat to humanity. To fight these bacteria, many scientists started studying various chemical and biological properties of these bacteria and develop various antibiotics to fight these organisms. In the data, the bacteria are classified into two types based on the Gram-Staining method. Gram-StainingGram-Staining is a method that can classify bacteria into two major types: Gram-Positive Bacteria and Gram-Negative Bacteria. Gram Positive bacteria have a thick layer of peptidoglycan (a cell wall) which gives a violet stain, whereas the Gram-Negative Bacteria have thinner peptidoglycan. Gram-Negative Bacteria have a cell membrane (not to be confused with the cell wall) that protects the inner parts of bacteria. Minimum Inhibitory Concentration (MIC)MIC is the minimum concentration of drug that prevents the growth of bacteria. It is often expressed in micrograms per milliliter (μg/mL) or milligrams per liter (mg/L). The lower the MIC, the better the antibiotic works against the respective bacteria. Goals and Purpose
Design choicesType of Visualization
ColorsUse of the Viridis colors(the midpoint and the extreme ends of the Viridis scale) to facilitate color-blind people to visually distinguish the colors. The same color is used for the same antibiotic to avoid any confusion.
Inference
Tools Used
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Name- Khushee A Namdeo
(Notebook link: https://colab.research.google.com/drive/13pz-kPkgW9CxKgMuEojMzPlHUx9W7RaM?usp=sharing) AIM OF VIZUALIZATION: DESIGN DECISIONS: SCALE, VISUAL ENCODING AND COLOR: The particular graph (grouped bar chart) is appropriate for this problem statement because it clearly communicates the relationships and variations between the three antibiotics (Penicillin, Streptomycin, and Neomycin) and their minimum inhibitory concentrations (MIC) values on 16 different bacteria when taking into account the Gram staining data. WHY THIS PARTICULAR ILLUSTRATION? (CHOICE OF GRAPH): EFFECTIVE COMMUNICATION: |
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Name : Faizan Mulla DESCRIPTIONThe chosen visualization is a pair of grouped bar plots, representing the minimum inhibitory concentration (MIC) of three antibiotics across different types of bacteria, segregated by their Gram staining property into two distinct subplots: one for Gram-positive bacteria and one for Gram-negative bacteria. The x-axis represents different types of bacteria and the y-axis denotes the MIC on a logarithmic scale. Each antibiotic is differentiated by color, as indicated in the legend. CHOICE of visualizationThe grouped bar plots were chosen to allow direct comparison of the antibiotics' effectiveness on each bacteria type. The logarithmic scale for MIC values accommodates the wide range of MIC values, allowing for meaningful comparison. The division of bacteria into two categories (Gram-positive and Gram-negative) provides a cleaner representation of the Gram staining property and reduces clutter in the visualization. INSIGHTS gathered / Observations:
CRITIC of visualization :
SUGGESTIONS for the visualization :
**SUMMARY / OVERVIEW : **In summary, the visualization design choices were driven by the goal of effectively comparing the antibiotics' effectiveness on different bacteria, while also cleanly representing the Gram staining property. The decisions regarding visualization type, scale, color, and data transformation were taken to facilitate a clear, uncluttered, and informative visualization of the dataset.
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Name: Srivinay Sridhar Visualization type: Grouped Bar charts Note: Due to the size of the image, it is better to view it in a separate tab.
Visualization of the concentrate effectiveness of Antibiotics on Gram-positive and negative bacteriaIntroductionAntibiotics are a class of powerful medications used to treat bacterial infections in both humans and animals. Different antibiotics target specific types of bacteria, and their effectiveness can vary depending on whether the bacteria are Gram-positive or Gram-negative. Bacteria that are stained dark blue or violet are Gram-positive. Otherwise, they are Gram-negative. The Minimum Inhibitory Concentration (MIC) is the smallest amount of an antibiotic needed to stop the growth of a specific germ under specific conditions. The data and purposeThe Minimum Inhibitory Concentration (MIC) of Penicillin, Streptomycin, and Neomycin is available for 16 bacteria; 9 of which are Gram-negative and the remaining 7 are Gram-positive. The purpose of visualizing this dataset is to compare the MIC values of the 3 antibiotics for Gram-positive and Gram-negative bacteria while also understanding how different bacteria of same type have different values of MIC. Since MIC is inversly proportional to the effectiveness of an antibiotic on bacteria, I felt the need to derive the Concentrate effectiveness (in %) for the antibiotics which is directly proportional to the effectivess. Visualization choiceThe choice of using grouped bar charts was a rational one as it makes it easier to compare the values across various bacteria types while referring to the same antibiotic on the same scale with colour coded bars. The split of the visualization between Gram-positive and negative is because we can see a stark difference in the concentration values if any and it makes it easier to compare across the two groups. The x-axis marks the 3 antibiotics while the y-axis marks the Concentration effectiveness (in %). Derived metric: The colour palatte used is pleasing to the eye and intentionally chosen so that the colours do not appear too bright and convey any wrong messages. They also belong to different spectrums and thus are easy to distinguish. Though the height of the bar only marks the concentrate effectiveness, the actual MIC values have been annotated on top of the bars to make sure the visualization is not only good looking but also contains all the information that is important. The visualization has also been sorted by the concentrate effectiveness of Penicillin (pink colour) which also happens to be the 1st index in the x-axis for better readability. This was also a conscious decision as the variance of MIC of Penicillin is the highest among the 3 antibiotics. Insights
Tools used
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Name : M.S.Srinivass
Data The given data contains the MIC values of 3 antibiotics on 16 different types of bacteria, out of which a few are gram positive and the rest are gram negative. The antibiotics are penicillin , streptomycin and neomycin. MIC or Choice of Visualization A grouped column chart was chosen and the data was split into 2 graphs, one having the gram positive bacteria and the other having the gram negative bacteria. All MIC values were also converted to the logarithmic scale ( natural log ) so as to scale down some high values and to visualize it better, This way the reader can see that a very well performing antibiotic for a particular bacteria would have its column on the negative Y-axis and a relatively poorly performing antibiotic would have a column on the positive Y-axis. A dark background with white text and light shades of red, green and blue were chosen for the columns representing the antibiotics. This makes the graph legible and pleasing to look at. X-axis represents the bacteria and Y-axis represents the MIC values. Insights From the visual we can see that :
Tools Used
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Name - Barun Kumar Sinha Performance of 3 most popular Antibiotics minimum inhibitory concentration (MIC) on 16 Bacteria
GoalDetermining which antibiotics (and how much concentration) is required to prevent growth in vitro. Design choiceI choose bubble chart because of the two variables (i.e., minimum inhibitory concentration, gram staining) used in determining the efficiency of the antibiotics on each bacteria . We represent the efficiency as a bubble, bubble color will determine the gram stain and size of the bubble will represent the concentration of the antibiotic . Visual Encodings
Observation
Tools used
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Antibiotic Effectiveness on BacteriaName: Prateek Ganguli
URL: https://public.tableau.com/views/BacteriavsAntibiotic/Bacteria_vs_Antibiotic OverviewFor this task, I have chosen to create a grouped bar chart to effectively communicate the data. Design Rationale
Data CommunicatedThe grouped bar chart will effectively convey the following aspects of the data:
Potential Limitations:While the grouped bar chart is a suitable choice for this dataset, it may have some limitations:
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Name - Priyanka Mazumdar Data Visualization Regarding Butin Antibiotic Data
Information About the Data & VisualizationAntibiotics are a class of medications that are used to treat bacterial infections. The data provided to us has various parameters which are significant:
Values that the visualization tries to show is the lowest MIC value for a particular bacteria with the use of a specific antibiotic because then it refers to that antibiotic being most appropriate for treatment. Design Principles used & their Benefits1. Type of visualization 2. Gridlines and Axes used 3. Colours used 5. Markers used 6. Sorting used Insights obtained from the Visualization
Limitations of the Design
Tools used
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Vineeth Reddy Donthi Antibiotic Effectiveness Across Bacterial Strains
Introduction-Minimum Inhibitory Concentration (MIC) is a crucial measure in microbiology, determining the lowest concentration of an antimicrobial needed to inhibit bacterial growth. It guides antibiotic selection for infections, and monitoring MIC changes aids in tracking antibiotic resistance. Gram staining classifies bacteria into Gram-positive and Gram-negative groups based on cell wall characteristics. This rapid technique aids in diagnosing infections, selecting appropriate antibiotics, and providing valuable insights into bacterial identification. The dataset provides information about the Minimum Inhibitory Concentration (MIC) values of three different antibiotics - Penicillin, Streptomycin, and Neomycin. The dataset also includes the Gram Staining reaction for each bacterium, indicating whether they are Gram-positive or Gram-negative. Design Choices-1. Type of visualization The purpose of using a logarithmic horizontal bar chart is to visualize data that spans a wide range of values, particularly when there is a significant difference between the magnitudes of the data points. The logarithmic scale compresses the data, making it easier to compare values that vary greatly in size on the same chart. 2. Colors, size Penicillin is denoted by blue color, Streptomycin by orange color and Neomycin by grey color. Axis labels have a font size of 12 to be easily readable without being too distracting. Data labels have a font size of 14 to stand out. Inference-The antibiotic with the lowest MIC value against a specific bacterial strain is generally considered the most effective. A lower MIC indicates that a smaller concentration of the antibiotic is required to inhibit bacterial growth, making it more potent against that particular strain. Tools Used-Google Sheets |
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Name : Varnika Bagaria Overview:In this task, I have used Google Colab and Google Sheets to obtain the chart. I have chosen to use a scatter chart. The given data has MIC values of 3 antibiotics on 16 types of bacteria. I first went about normalizing the values and then plotting it. Choice of visualization
Chart
Shortcomings
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Name : Harshad Shahu Paikrao
Link to the visualization : https://public.tableau.com/app/profile/harshad.paikrao/viz/DatavizGA3/Sheet1?publish=yes Overview:The given dataset contains the minimum inhibitory concentration (MIC) values of the three most popular antibiotics on 16 different types of bacteria. Along with the gram staining test effect of each bacteria. The purpose of the visualization is to effectively highlight the most effective antibiotic for each of the 16 types of bacteria. The target audience is medical professionals. Design Decision:Type of visualization:
Color and labels:
Tools used
Inference:
Shortcomings
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Visualisation on effectiveness of antibioticsCreated by: Afnan Ahmad | 21F1003730
ObjectiveThe aim of this visualization is to help in comparing the effectiveness of three antibiotics, namely, Penicillin, Streptomycin, and Neomycin against 16 different bacteria. Minimum Inhibitory Concentration (MIC) is used as the measure of effectiveness. Design DecisionsThe design choices have been made, keeping in the mind the following principles:
Visual EncodingsType of Visualization: A stacked bar chart has been used for this visualization, because it allows us to easily compare the concentration values across the different antibiotics. Furthermore, distinct colors have been used to represent the antibiotics, it allows us to quickly see the most ineffective (high concentration) and effective (low concentration) antibiotics for a particular bacterium. Colors: Bright yet low saturation colors have been used as they are easier on the eyes, while allowing us to easily differentiate between them. Grouping: One of the unique key features of this visualization is that colors have been used to group the labels (on the y-axis) representing the names of bacteria. The labels have been sorted and grouped according to the gram-staining characteristic, i.e. gram-positive or gram-negative. Furthermore, legends have been added accordingly to convey the meaning behind the groups. Data TransformationThe minimum inhibitory concentration (MIC) is represented on the chart in a logarithmic scale so that the numbers are normalized and are on the same scale, allowing us to compare between them. ShortcomingsPrimarily, the fact that lower concentration is better might not be apparent at first glance, leading possibly to wrong conclusions. Although, this issue has been mitigated to some extent by mentioning on the chart that lower is better, a different encoding may possibly be used to convey this more clearly. It should be noted however that, as mentioned in design decisions, the design assumes basic familiarity with the objective of this visualization as well as the measure used herein. Therefore, it is expected that the intended audience would be able to interpret it properly. Tools UsedMicrosoft Excel |
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Name : Vishvam Sundararajan S Visualization on Effectiveness of AntibioticsNote that the MIC column is normalized (between 0 and 1) for better visualization
Aim of the VisualizationThe aim of this visualization is to help in comparing the effectiveness of three antibiotics, namely, Penicillin, Streptomycin, and Neomycin against 16 different bacteria. Minimum Inhibitory Concentration (MIC) is used as the measure of effectiveness. Type of Visualization UsedHeatmap Why I Went With This
Design Decisions
Tools Used
Code Used To Generate The Visualization : import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
# Renamed the given file to data.xlsx
df = pd.read_excel('data.xlsx')
# Normalize the MIC column
min_mic = df[['Penicilin', 'Streptomycin', 'Neomycin']].min().min()
max_mic = df[['Penicilin', 'Streptomycin', 'Neomycin']].max().max()
df[['Penicilin', 'Streptomycin', 'Neomycin']] = (
df[['Penicilin', 'Streptomycin', 'Neomycin']] - min_mic) / (max_mic - min_mic)
)
# Pivot the dataframe to have antibiotics as columns,
# bacteria as rows, and normalized MIC values as values
pivot_df = df.pivot(
index='Bacteria', columns='Gram Staining',
values=['Penicilin', 'Streptomycin', 'Neomycin']
)
plt.figure(figsize=(10, 16))
sns.heatmap(
pivot_df, cmap='mako_r', annot=True,
fmt=".2f", linewidths=0.5,
cbar_kws={'label': 'Normalized MIC'}
)
plt.title(
'Effectiveness of Antibiotics Against Bacterial Infections', pad=40
)
plt.xlabel('Gram Staining', labelpad=24)
plt.ylabel('Bacteria', labelpad=24)
plt.show() |
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Roll No: 21F1001178, Hitansh Shah Chart Design Rationale: Visual Encodings: X-axis: The X-axis represents the 16 bacterial infections, labeled with their names for easy identification. Grouped bar chart: This chart type facilitates easy comparison of multiple categories (bacteria) across different subgroups (antibiotics) at once, enabling viewers to identify the most effective antibiotic for each bacterial infection quickly.
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Data Viz of Antibiotic Effectiveness on BacteriaName : Dipak Patil Objective:The objective of this data visualization is to effectively communicate the antibiotic effectiveness (minimum inhibitory concentration - MIC) of the three most popular antibiotics (Penicillin, Streptomycin, and Neomycin) against 16 bacterial infections. The visualization should allow an easy comparison of antibiotic efficacy for each bacterium and highlight any patterns related to Gram staining (Gram-positive or Gram-negative).
Design Decisions:
Tools Used:Tableau Public was utilized to create the data visualization. Tableau is a powerful data visualization tool that allows for easy exploration and representation of data through interactive charts and graphs. Conclusion:In conclusion, the stacked bar plot with rings, using a logarithmic scale and distinct color scheme, created using Tableau Public, effectively communicates the antibiotic effectiveness data. The visualization enables viewers to compare the efficacy of Penicillin, Streptomycin, and Neomycin against different bacterial infections and easily identify patterns related to Gram staining. The use of rings as marks and appropriate color choices enhances visibility and aids in the quick understanding of the data. While this design presents the data well, it's essential to consider potential limitations related to clutter and perception of size. Overall, the visualization serves its objective by providing valuable insights into antibiotic efficacy and its relationship with bacterial infections and Gram staining. |
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Manisha Bapat Brief Information:- Gram-Staining: Objective: Observations:
Rationale to choose Area chart
Shortcomings:
For Gram Positive :
For Gram Negative:
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Name: Siddhi Dhirajkumar Pandirkar
Tool: MS Excel Design Decisions Downplayed Information Improvements References: |
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Srijan Shukla Clustered Bar Chart: In this clustered bar chart, each bacteria is represented on the x-axis, and the minimum inhibitory concentration (MIC) values of the three antibiotics are shown as grouped bars for each bacteria. The y-axis represents the MIC values. The three antibiotics (Penicillin, Streptomycin, and Neomycin) are color-coded and distinguished using the legend. To add the information about the Gram staining reaction, we used text annotations below each bar group. Gram-positive bacteria are labeled as "Gram-positive," and Gram-negative bacteria are labeled as "Gram-negative." The choice of a clustered bar chart is appropriate because it allows us to compare the MIC values of multiple antibiotics for each bacteria while also considering the Gram staining information. The grouping of bars for each bacteria helps in easy visual comparison of the antibiotic effectiveness, and the text annotations provide additional insight into the Gram staining reaction of each bacteria. The chart's title, axis labels, and legend provide context and improve the chart's interpretability. Pie Chart: Each pie chart represents one antibiotic, and it is divided into two segments: one for Gram-negative bacteria and another for Gram-positive bacteria. The size of each segment corresponds to the percentage of bacteria with that particular Gram Staining reaction relative to the total number of bacteria affected by the antibiotic. By using pie charts for each antibiotic, we can quickly compare the Gram Staining distributions across different antibiotics and identify any patterns or trends. This visualization helps us understand how the effectiveness of each antibiotic relates to the Gram Staining reaction of the bacteria it targets. Stackplot: The purpose of the stackplot is to visualize the contribution of each antibiotic to the overall effectiveness for each bacterium. It allows us to observe how the cumulative effectiveness of the three antibiotics varies across different bacteria. Additionally, the stackplot helps in identifying the dominant antibiotics that contribute the most to the overall effectiveness for each bacterium. This visualization is useful for comparing the combined effects of multiple antibiotics and gaining insights into which bacteria are more susceptible to the combined treatment of these antibiotics. Line Chart: The line chart allows us to observe how the MIC values change for each antibiotic as we move from one bacterium to another. It helps in identifying patterns and trends in the data, such as which antibiotics tend to be more effective against certain bacteria. This type of visualization is useful when we want to focus on the trend of MIC values and how they vary across the different bacteria in the dataset. |
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Uday Patil 21f1003481 Findings: The chart illustrates the performance of three antibiotics on 16 different bacteria strains, highlighting the MIC values for each combination. The horizontal axis represents the MIC values which are color-coded, while the vertical axis shows the bacteria. Analysis: The chart reveals intriguing patterns regarding antibiotic efficacy against specific bacterial strains. Penicilin demonstrates remarkable effectiveness against Gram-positive bacteria, as evidenced by consistently lower MIC values for these strains. However, its performance against Gram-negative bacteria is comparatively weaker, necessitating higher concentrations to inhibit growth. In contrast, Neomycin appears to have a more balanced performance, showing moderate MIC values for both Gram-positive and Gram-negative bacteria. This characteristic could make it a versatile choice for treating a broader range of infections. Streptomycin, on the other hand, exhibits a significant advantage in tackling Gram-negative bacteria, with notably lower MIC values in comparison to the other antibiotics. Nevertheless, its potency against Gram-positive bacteria is less impressive. For Gram Positive : For Gram Negative: |
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-- ObjectiveCompare the effect of 3 antibodies (Penicillin, Streptomycin, and Neomycin) on different types of bacteria and find which antibody is most effective against a bacteria. Also, identify any gross patterns, such as a strain of bacteria more susceptible to an antibody. InformationMIC, or minimum inhibitory concentration, is a measure used in microbiology and pharmacology to assess the effectiveness of antimicrobial agents, such as antibiotics or antifungal drugs. It refers to the lowest concentration of a drug required to inhibit the visible growth of a microorganism, specifically a bacterium or fungus, in a controlled environment in vitro (in a laboratory setting). Lower concentration indicates better effectiveness. Gram-positive bacteria retain the purple stain, while Gram-negative bacteria appear pink. This difference is due to the variation in their cell wall structures. Gram-positive bacteria have a thick peptidoglycan layer, while Gram-negative bacteria have a thinner peptidoglycan layer between two membranes. This distinction influences their susceptibility to antibiotics and their ability to cause infections. Design DecisionI wanted an overall view of all the bacteria reacting to the antibiotics and also wanted to compare their effectiveness between the strains. I have created a Grouped Scatter Plot and color-coded the 3 antibiotics as follows: Penicillin - Orange, Streptomycin - Blue, and Neomycin - Red. The below 2 charts also follow the same color coding. All the charts' axes have been scaled to logarithmic values ranging from 0.001 to 1000 to compare the effectiveness of all antibodies. The bacteria have been sorted based on descending values of MIC. Tools UsedI used Tableau for creating this dashboard. Findings
ConclusionThe visualization effectively conveys the information encoded in the data. The logarithmic scaling helps the patterns come out, and the comparison within gram strains shows the effectiveness of each antibody within a class of bacteria. The Grouped Scatter Plot with color-coded circle marks for different antibodies is aesthetically pleasing and also shows the trend of the data. |
Shreya Y
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Farid Khan 
Understanding of the Problem
Purpose
Design Decisions
Color Encoding
ObservationsThe 3 antibiotics that prevent the bacteria with highest effectiveness are given below: Positive Gram Straining
Negative Gram Straining
To conclude Neomycin is the most effective antibiotic, as it prevents both the Gram Straining bacteria with the least concentration Tools usedThe Radial Tree visualization from Flourish has been used. |
and others
After World War II, antibiotics were considered "wonder drugs", since they were easy cures for what had been intractable ailments. To learn which drug worked most effectively for which bacterial infection, the performance of the three most popular antibiotics on 16 bacteria was gathered. The values in the table represent the minimum inhibitory concentration (MIC), a measure of the effectiveness of the antibiotic, which represents the concentration of antibiotic required to prevent growth in vitro. The reaction of the bacteria to Gram staining is described by the covariate “gram staining”. Bacteria that are stained dark blue or violet are Gram-positive. Otherwise, they are Gram-negative.
Your task is to design a chart that you believe effectively communicates the data and provide a short write-up (no more than 4 paragraphs) describing your design.
As different visualizations can emphasize different aspects of a data set, you should document what aspects of the data you are attempting to most effectively communicate. Just as important, also note which aspects of the data might be obscured or downplayed due to your visualization design.
In your write-up, you should provide a rigorous rationale for your design decisions. Document the visual encodings you used and why they are appropriate for the data. These decisions include the choice of visualization type, size, color, scale, and other visual elements, as well as the use of sorting or other data transformations. How do these decisions facilitate effective communication?
Here is the link for the dataset: Butin_antibiotic_data.xlsx
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