Lab1: Introduction to Data Analysis

Course: INF-604: Data Analysis
Lecturer: Sothea HAS, PhD

Objective: You have already seen some elements of Data Analysis in the course. In this lab, we will take our first step into working with the main element of Data Analysis, which is the dataset. By the end of this lab, you will be able to import data into a Jupyter Notebook and perform some data manipulation.

The notebook of this Lab can be downloaded here: Lab1_Introduction.ipynb.
Or you can work directly with Google Colab here: Lab1_Introduction.ipynb.

Student’s name: …
Year: …
Major: …

1. Data for Your Business

Imagine you want to start your own business, such as a coffee shop or a bookstore. What types of data do you think you need to gather to determine the potential success of your business? Here are some questions to help you think and answer this question:

What is your plan for the business?
What information might you need to collect? What is the size of the data?
Where do you think you can find this information?
What might go wrong with the collected data?
What step do we need to handle this problem?

Answer:

2. Importing Some Data

There are many online data sources that you can explore, and one of the most popular is Kaggle. In addition to datasets, Kaggle also hosts data competitions with prizes and offers courses to help you advance in data learning.

Here, we start our journey by exploring a dataset that you probably have heard its name before: Titanic. You can download it from Kaggle using the following codes.

# %pip install kagglehub

import kagglehub

# Download latest version
path = kagglehub.dataset_download("yasserh/titanic-dataset")


# Pandas module allows you to import the data
import pandas as pd
data = pd.read_csv(path+'/Titanic-Dataset.csv')
data.head()

	PassengerId	Survived	Pclass	Name	Sex	Age	SibSp	Ticket	Fare	Cabin	Embarked
0	1	0	3	Braund, Mr. Owen Harris	male	22.0	1	A/5 21171	7.2500	NaN	S
1	2	1	1	Cumings, Mrs. John Bradley (Florence Briggs Th...	female	38.0	1	PC 17599	71.2833	C85	C
2	3	1	3	Heikkinen, Miss. Laina	female	26.0	0	STON/O2. 3101282	7.9250	NaN	S
3	4	1	1	Futrelle, Mrs. Jacques Heath (Lily May Peel)	female	35.0	1	113803	53.1000	C123	S
4	5	0	3	Allen, Mr. William Henry	male	35.0	0	373450	8.0500	NaN	S

2.1. Overview of the data

Answer the following questions:

A. How many rows and columns are there in this dataset?

B. Explain the meaning of each column.

C. Are there any missing values in this dataset? If so, how many rows contain at least one missing value?

What should you do with column Cabin?
How would you drop rows with at least one missing value?

# Let's find out!

2.2. Single information

D. How many male and female passengers were on the ship?

E. How many of them survived? How many didn’t?

F. How many passengers were younger than 3 years old? How many were older than 60 years old?

G. How many passengers embarked from the three ports?

C: Cherbourg, France.
Q: Queentown, Ireland.
S: Southampton, England.

H. How many passengers were in the 1st, 2nd and 3rd class?

# To do

2.3. Multiple information

I. How many 1st class passengers survived? How about 2nd and 3rd class?

J. How many female passengers survived? How many males did?

K. How many people from each embarkation port survived?

L. Was Jack on the ship? How about Rose?

1. Data for Your Business

2. Importing Some Data

2.1. Overview of the data

2.2. Single information

2.3. Multiple information

Further Reading