IE6400 Foundations Data Analytics Engineering
Fall Semester 2023
Quiz 6: Day8: Exploratory Data Analysis (EDA)
Question 1: Load the Dataset
•
Load the dataset ‘dataset.csv’ into a pandas DataFrame and display the first five rows.
Check the general structure of the DataFrame.
Question 2: Summary Statistics
•
Display the summary statistics of the dataset. This includes count, mean, standard
deviation, minimum, 25th percentile, median (50th percentile), 75th percentile, and
maximum for numerical columns.
Question 3: Handling Missing Values
•
Determine the number of missing values in each column of the dataset. Handle the
missing values by replacing them with the mean of the respective column.
Question 4: Data Visualization
•
Visualize the distribution of the Age, Height, and Weight columns using appropriate
plots. Analyze the distributions and note any observations.
Question 5: Correlation Analysis
•
Calculate and display the correlation matrix of the numerical columns in the dataset (Age,
height, and weight). Analyze the relationships between these numerical variables.
Question 6: Gender Distribution
•
Plot a bar graph to visualize the distribution of the Gender column. How many males and
females are present in the dataset?
Question 7: Age Group Analysis
•
Categorize the Age column into different age groups (for example, 20-30, 31-40, etc.)
and visualize the distribution of age groups.
Question 8: Height-Weight Relationship
•
Create a scatter plot to visualize the relationship between Height and Weight. Is there any
visible correlation between them?
Question 9: Outlier Detection
•
Use appropriate plots to detect outliers in the Height and Weight columns. Are there any
outliers present?
Question 10: Insights and Observations
•
Provide any additional insights and observations from the dataset after performing the
above tasks.
