presentation

1.

TITLE: GLOBAL BUSINESS INSIGHTS:
ANALYZING HISTORICAL AND MISSING
BUSINESS DATA
Presented by: Rafael Xudoynazarov
Date: 23.11.2024

2.

DATA ANALYSIS OF BUSINESS AND
COUNTRY DATA
Introduction
This presentation explains a Python script designed to analyze business and country data to answer three
key questions:
1. What is the oldest business on each continent?
2. How many countries are missing business data per continent, both before and after including new
businesses?
3. What is the oldest business category by continent?
By leveraging pandas for data manipulation, we merge and analyze datasets to extract meaningful
insights.

3.

DATA LOADING
• First, we import the necessary library and load the datasets:

4.

DATA PREPARATION
Combining Business Data
We combine the original and new businesses into a single DataFrame:
Purpose: To ensure that our analysis includes all available business data.
Merging with Countries and Categories
We merge the combined business data with country and category information:
Purpose: To enrich the business data with country and category details for comprehensive analysis.

5.

QUESTION 1: OLDEST BUSINESS ON EACH CONTINENT
1. Group by Continent: We group the merged data by the continent column.
2. Find Oldest Business: For each continent, we find the business with the earliest year_founded.
3. Select Relevant Columns: We extract the continent, country, business, and year_founded columns.

6.

Q.1 DISPLAYING AND OUTPUT
• Results:
• Output:
• Interpretation: The table lists the oldest business on each continent, providing insights into historical business
establishments globally.

7.

QUESTION 2: COUNTRIES MISSING BUSINESS DATA PER CONTINENT
Finding Countries Without Business Data in the Original Dataset
1. Identify Missing Countries: We find countries not represented in the businesses DataFrame.
2. Count by Continent: We count the number of missing countries per continent.

8.

Q.2 DISPLAYING AND OUTPUT
3. Display Results:
Output:

9.

Q.2 INCLUDING NEW BUSINESSES
We repeat the process after including new_businesses:
1. Update Missing Countries:
2. Recount by Continent:
3. Display Updated Results:
Output
Interpretation
Before Including New Businesses: Several countries per
continent lacked business data.
After Including New Businesses: The number of countries
missing data decreased, indicating improved data coverage.

10.

QUESTION 3: OLDEST BUSINESS CATEGORY BY CONTINENT
1. Group by Continent and Category: We group the data by both continent and category.
2. Find Oldest Year: For each group, we find the earliest year_founded.
3. Sort Results: We sort the data by continent and year_founded for readability.

11.

Q.3 DISPLAYING AND OUTPUT
• Results:
• Output:

12.

Thank You!
Questions?