Data Engineering and Analytics(ELGE-1B) — DU B. Sc. (Hons) Electronics Previous Year Question Papers

(c) Load a dataset from a CSV file using Pandas. Perform basic data cleaning by handling any missing values and renaming columns where necessary. Display the final Data Frame. (6) 7. (a) Using Matplotlib, create a histogram for any numerical variable in a dataset of your choice. Label the axes, add a title, and describe what the histogram reveals about the data distribution. (b) Differentiate between "Series" and "DataFrame" in Pandas. Can we use a dictionary datatype to create a DataFrame? Explain. 1. (a) Describe the purpose of scipy stats and provide an example of a statistical function it offers. (b) Describe thę meaning of the term 'p-hacking'. (c) Define mean, median, and mode, and explain their differences. (3) (d) Draw the block diagram of ETL pipeline architecture. (3) (e) What do you understand by the term Data (f) Explain the purpose of nplinspace() and provide a scenario where it would be useful. (3) 2. (a) In the population, the average IQ is 115 with a standard deviation of 15. A team of scientists wants to test a new medication to see if it has either a positive or negative effect on intelligence, or no effect at all. A sample of 30 participants who have taken the medication has a mean of 140. Did the medication affect intelligence? Consumer_ID | Name Order ID | Consumer_ID Amount Data Set-l Data Set-ll (c) Load the following retail data into a DataFrame, then use the groupby() function to group data by Store and calculate the total Revenue for each store. Display the grouped DataFrame. (6) Store Product Revenue Store1 Shoes 1500 "'' Store1 Bags 1000 Store2 Shoes 2000 Store2R Bags 1.200 6. (a) Using NumPy, create a 3x3 matrix with random integers between 1 and 10. Calculate and display the mean, standard deviation, and variance for each row and column. (6) (b) Describe the five V's of Big Data (Volume, Velocity, Variety, Veracity, and Value). Explain how these traits impact data storage and processing. (6) (c) Generate a line plot to visualize a time series of daily temperature data. Assume you have a DataFrame df with a Date and Temperature columns. (6) (i) Convert the Date column to a DateTime format. (ii) Plot the Temperature data against Date, setting appropriate labels for the axes and a title "Daily Temperature Over Time". 5. (a) Given the following sales data, use Pandas to calculate the mean, median, and standard deviation for each numerical column and interpret the results. (b) Given the two datasets below, perform an inner join on Customer_ID and display the merged (b) A company has two departments, Sales and Marketing, with each department hiring male and female employees. The company wants to analyze the success rate (number of successful hires) in each department by gender. (9) (i) Calculate the success rate of hires for each gender (male and female) in each department separately. (ii) Calculate the overall success rate of hires for males and females across both departments combined.