Data Analysis and Visualization using Python — DU B.Sc. (Hons) Computer Science Previous Year Question Papers

This question paper has two Sections A and B. Parts of a question must be attempted together. Section A carries 30 marks and each question in Section B carries 15 marks. Assume numpy has been imported as np and pandas has been imported as pd. 1. (a) Given an array marks : marks = np.array ([55, 72, 88, 45, 67, 90, 34, 76, 81]) Write Python code for the following : (i) Print marks greater than 60. (ii) Print marks that are odd numbers. (iii) Reshape the array into a 3 × 3 array named marks_2D. (b) Write Python commands to create a Series named S with values [5, 6, 7, 8] and index [1, 2, 3, 4] and then rename index 1 to ‘one’. (3) (c) Write Python statements to create a 3 x 3 matrix using arange() in NumPy such that the matrix contains numbers from 1 to 9 arranged row-wise. Also, print its transpose. (3) (d) What is the purpose of legend in plotting? Explain with an appropriate example. (3) (e) Differentiate between loc() and iloc() with the help of a suitable example. (f) Create a DataFrame having 6 rows and 3 columns and populate it with random values in the range 10 to 50. Set the row index as [‘A’, ‘B’, ‘C’, ‘D’, ‘E’, ‘F’] and column names as [‘X’, ‘Y’, ‘Z’]. (3) (g) Write a command to merge the two given DataFrames df1 and df2 based on a common column Student_ID. (3) 'Name': ['Amit', 'Neha', 'Ravi', 'Sara'] (h) Differentiate between a series and a DataFrame. (3) (i) A retail store maintains a customer database containing fields such as customer name, membership type, number of purchases, annual spending, and customer satisfaction level. Classify each field as either qualitative or quantitative data. (3) (j) What is correlation? How does it help in understanding relationships between two variables? Mention the name of the command used to calculate correlation. (3) 2. (a) What is hierarchical indexing (Multiindex) in Pandas? Explainhow to create and access data using hierarchical indexing. (5) (b) List and describe the steps involved in process of Data Analysis. (5) (c) You are given the following DataFrame : (5) 'Month': ['Jan', 'Feb', 'Jan', 'Feb', 'Mar', 'Mar'], df = pd.DataFrame(data) Write the code for the following : (i) Create a pivot table showing total sales of each product. (ii) Add total (margins) to the pivot table. (iii) Create a cross-tabulation showing the frequency of Product across different Months. 3. (a) Write the code to create a line plot using the following data: import matplotlib.pyplot as pit months = [‘Jan’, ‘Feb’, ‘Mar’, ‘Apr’] (5) Use Specifications : Line color: blue and style: dashed (--) Markers: circle (o) with size 8 Line width: 2 Title: “Monthly Sales Trend” X-axis label: “Months”, Y-axis label: “Sales” Display the plot (b) You are given the following DataFrame: data = { (5) df = pd.DataFrame(data, index=['Alice', 'Bob']) Answer the following : (i) Write the output of: df.stack() (ii) Write the output of: df.unstack() (iii) Briefly explain the functioning of stack() and unstack().