ids706-week9-notebook

Week 9: Cloud-Hosted Notebook Data Manipulation

Requirements

Set up a cloud-hosted Jupyter Notebook (e.g., Google Colab)
Perform data manipulation tasks on a sample dataset

Grading Criteria

Setup and configuration (20 points)
Data manipulation tasks (20 points)

Deliverables

Link to the cloud-hosted notebook
Document or video demonstrating the tasks performed

1. Setup and Configuration

Using Google Colab:

Navigate to Google Colab.
Choose File -> New notebook.
A new Jupyter Notebook will be launched in your browser, leveraging Google's cloud infrastructure.

2. Data Manipulation Tasks

For the purposes of this demonstration, we'll assume a simple CSV dataset. Below is an outline of the data manipulation tasks performed:

2.1 Import Necessary Libraries

import pandas as pd

2.2 Create a Simple Dataset

data = {
    'Name': ['Alice', 'Bob', 'Charlie', 'David'],
    'Age': [25, 30, 35, 40],
    'Salary': [50000, 60000, 70000, 80000]
}

df = pd.DataFrame(data)

2.3 Display the Dataset

print(df)

2.4 Filter Employees Older Than 30

print(df[df['Age'] > 30])

2.5 Calculate the Average Salary

print(df['Salary'].mean())

2.6 Add a New Employee

new_employee = pd.DataFrame({'Name': ['Eva'], 'Age': [28], 'Salary': [55000]})
df = pd.concat([df, new_employee], ignore_index=True)
print(df)

3. Deliverables

Link to the cloud-hosted notebook: [https://colab.research.google.com/github/casnz1601/ids706-week9-notebook/blob/main/data-manipulation.ipynb]
This README.md file demonstrates the tasks performed.

casnz1601 / ids706-week9-notebook