DADS301 PROGRAMMING IN DATA SCIENCE

Description

SESSION	JUL – AUG 2024
PROGRAM	MASTER OF BUSINESS ADMINISTRATION (MBA)
SEMESTER	III
COURSE CODE & NAME	DADS301 PROGRAMMING IN DATA SCIENCE

 

 

Assignment Set – 1

 

1. (a) What is Data wrangling? Name the package used for Data wrangling in R and describe some of its features.

(b) What are vectors? Explain the creation of vectors with examples. Also, describe how to identify and handle missing values.          

Ans 1. Data Wrangling and Vectors in R

(a) Data Wrangling

Data wrangling, also known as data munging, is the process of cleaning, structuring, and enriching raw data into a desired format for better decision-making. This process is critical in data analysis as it ensures data is accurate, complete, and usable. The raw data collected from different sources often contains errors, inconsistencies, and missing values, which can hinder analysis. Data wrangling

 

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2. (a) Describe the steps to initialize a plot in R, specify aesthetics, create a simple plot, and add titles and labels to the plot in R.

(b) Explain the chaining operator with an example.         

Ans 2. Plot Initialization and Chaining Operators in R

(a) Initializing a Plot in R

Visualization is an essential part of data analysis, and R provides robust tools for creating plots. One of the most popular libraries for plotting in R is ggplot2, which is also part of the tidyverse. Creating a plot in ggplot2 involves several steps:

1. Load the Library: Before creating

 

 

3. (a) Explain with an example how box plots can be used to understand the relationship between continuous and categorical feature. What are the insights that can be derived from such plots.

(b) What is continuous random variable. How can that be created using R?

Ans 3. Box Plots and Continuous Random Variables

(a) Understanding Box Plots

Box plots are a powerful graphical tool used to summarize the distribution of a continuous variable while considering a categorical feature. They are also known as whisker plots and provide insights into data spread, central tendency, and potential outliers.

A box plot displays the following components:

1. Median: The line inside the box represents the median of the data.
2. Interquartile Range (IQR): The box itself spans the first quartile (Q1) to the third quartile (Q3), representing the middle 50

 

Assignment Set – 2

 

4. (a) Describe the need for Python and applications of Python.

(b) Explain with examples – Set, List and Tuples. What are the   similarities and differences among them?  5+5           

Ans 4. Python Applications and Data Structures

(a) The Need for Python

Python has emerged as one of the most popular programming languages due to its simplicity, versatility, and extensive libraries. Its growing prominence across industries stems from its ability to handle a variety of tasks, from web development to data analysis.

Why Python is Needed:

1. Ease of Learning: Python’s

 

5. (a) How are strings converted into iterables? Explain with an example how the iterables thus created can be iterated through.

(b) Explain how simple and complex pattern searches can be performed on lists.        

Ans 5. Strings as Iterables and Pattern Searches on Lists

(a) Strings as Iterables

In Python, strings are inherently iterable, meaning you can traverse each character in a string using an iterator or a loop. Converting a string into an iterable involves using the built-in iter() function, which creates an iterator object from the string. This iterator can then be used to traverse the string one character at

 

6. (a) What are Stacked Bar charts? When is it used? Explain with an example.

(b) Explain the merging of two data frames with similar name for the ‘join’ column and dissimilar names for the ‘join’ column.      

Ans 6. Stacked Bar Charts and Merging Data Frames

(a) Stacked Bar Charts

Stacked bar charts are a type of bar chart used to visualize the contribution of different components to a total over multiple categories. In a stacked bar chart, each bar is divided into segments representing individual components, stacked on top of each other. This allows for a clear comparison of both total values and