https://github.com/pradip-data/world-merchandise-trade
This project analyzes global merchandise trade trends from 1948 to 2023 using Google BigQuery and Python. It includes country-wise and product-wise trade performance, covering exports, imports, total trade, and trade deficit. The analysis features SQL queries for BigQuery, data visualizations, and detailed reports to uncover long-term trade pattern
https://github.com/pradip-data/world-merchandise-trade
datawarehouse google-biquery google-cloud-platform merchandise python python-visualization sql trade trade-data-1948-2023
Last synced: 21 days ago
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This project analyzes global merchandise trade trends from 1948 to 2023 using Google BigQuery and Python. It includes country-wise and product-wise trade performance, covering exports, imports, total trade, and trade deficit. The analysis features SQL queries for BigQuery, data visualizations, and detailed reports to uncover long-term trade pattern
- Host: GitHub
- URL: https://github.com/pradip-data/world-merchandise-trade
- Owner: pradip-data
- Created: 2025-03-01T16:34:43.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-04T09:54:19.000Z (over 1 year ago)
- Last Synced: 2025-08-10T16:34:02.360Z (10 months ago)
- Topics: datawarehouse, google-biquery, google-cloud-platform, merchandise, python, python-visualization, sql, trade, trade-data-1948-2023
- Language: Jupyter Notebook
- Homepage:
- Size: 30.2 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🌍 Global Merchandise Trade (1947-2023) Analysis using ChatGPT AI, Google BigQuery & Python
## 📌 Project Overview
This project analyzes **global merchandise trade trends from 1947 to 2023**, with a primary focus on **India's trade performance**. The dataset is sourced from **Google BigQuery** and consists of key indicators such as **exports, imports, total trade, and trade deficit** for different countries. The analysis leverages:
### 🚀 Technologies & Methodologies Used:
✅ **Google BigQuery** – Efficient data extraction & querying 📊
✅ **Python** – Data processing, transformation & visualization 🐍
✅ **ChatGPT AI** – AI-driven insights & trend analysis 🤖
✅ **Automated PDF Reports** – Structured storytelling with key findings 📄
---
## 🌍 Data Source
📌 The trade data used in this project is sourced from the **World Trade Organization (WTO)**.
🔗 **Official WTO Merchandise Trade Statistics:** [WTO Trade Data](https://www.wto.org/english/res_e/statis_e/merch_trade_stat_e.htm)
---
## 📊 Key Objectives
🔹 Analyze **India's exports, imports, total trade, and trade deficit** over time.
🔹 Compare **India's trade performance** against **global leaders**.
🔹 Identify **key trade trends, challenges, and opportunities** for improvement.
---
## 📊 Key Questions Analyzed
1️⃣ **How has global trade evolved from 1947 to 2023?**
2️⃣ **What is India’s trade performance in exports, imports, and total trade?**
3️⃣ **How has India’s trade deficit changed over time?**
4️⃣ **How does India compare with top exporting and importing nations?**
5️⃣ **What are the key challenges in India’s trade landscape?**
6️⃣ **What strategies can improve India’s trade competitiveness?**
---
## 📊 Dataset Overview
### 📂 Dataset Structure
| Column Name | Description |
|--------------------|------------------------------------|
| **IndicatorCode** | Unique code for trade indicators |
| **Indicator** | Type of trade (Exports/Imports) |
| **ReporterCountry** | Country reporting the trade |
| **Partner** | Trade partner country |
| **ProductCode** | Unique product identifier |
| **Product** | Name of traded product |
| **Year** | Trade year |
| **Value_MillionUSD** | Trade value in million USD |
---
## 📥 Installation
### 🚀 Clone the Repository
```bash
git clone https://github.com/yourusername/Global-Trade-Analysis.git
cd Global-Trade-Analysis
```
### 📦 Install Dependencies
```bash
pip install pandas matplotlib seaborn fpdf google-cloud-bigquery
```
### 🔑 Set Up Google BigQuery Credentials
1️⃣ Create a **Google Cloud Project**.
2️⃣ Enable **BigQuery API**.
3️⃣ Download your **service account JSON key** and set it as an environment variable:
```bash
export GOOGLE_APPLICATION_CREDENTIALS="path/to/your-key.json"
```
---
## 📜 Analysis & Code Overview
## 📌 Section A : Some BigQuery Code & Console Screenshots
### 1️⃣ Yearly Growth of Trade Value (1948-2023)
```sql
WITH YearlyTrade AS (
SELECT
Year,
SUM(Value_MillionUSD) AS Trade_Value
FROM `my-project-1711648161671.World_Trade.Countries_Merchandise_Trade`
WHERE Product="Total merchandise"
GROUP BY Year
)
SELECT
Year,
Trade_Value,
LAG(Trade_Value) OVER (ORDER BY Year) AS Prev_Year_Trade_Value,
ROUND(((Trade_Value - LAG(Trade_Value) OVER (ORDER BY Year)) / LAG(Trade_Value) OVER (ORDER BY Year)) * 100, 2) AS Growth_Percentage
FROM YearlyTrade
ORDER BY Year;
```
### 2️⃣ India's Total Trade Value (Exports + Imports) (1948-2023)
```sql
SELECT
Year,
SUM(Value_MillionUSD) AS Total_Trade_Value
FROM `my-project-1711648161671.World_Trade.Countries_Merchandise_Trade`
WHERE ReporterCountry = 'India' AND Product ="Total merchandise"
GROUP BY Year
ORDER BY Year;
```
### 3️⃣ India's Trade Deficit (1948-2023)
```sql
WITH IndiaTrade AS (
SELECT
Year,
SUM(CASE WHEN Indicator = 'exports' THEN Value_MillionUSD ELSE 0 END) AS India_Exports,
SUM(CASE WHEN Indicator = 'imports' THEN Value_MillionUSD ELSE 0 END) AS India_Imports
FROM `my-project-1711648161671.World_Trade.Countries_Merchandise_Trade`
WHERE ReporterCountry = 'India' AND Product ="Total merchandise"
GROUP BY Year
)
SELECT
Year,
India_Exports,
India_Imports,
(India_Imports - India_Exports) AS Trade_Deficit,
CASE
WHEN (India_Imports - India_Exports) > 0 THEN 'Trade Deficit'
ELSE 'Trade Surplus'
END AS Trade_Status
FROM IndiaTrade
ORDER BY Year;
```
## 📸 BigQuery Execution Screenshots
---
## 📌 Section B : Python Code & Visualizations
### 📊 Python Code for Data Visualization
```python
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from reportlab.lib.pagesizes import letter
from reportlab.pdfgen import canvas
# 📂 Load dataset
file_path = r"C:\Users\chemi\Downloads\PROJECT -World Merchandise Trade (Bigquery Project)\BigQuery Output Result\India's Global Trade Case Study (1948-2023).csv"
df = pd.read_csv(file_path)
# 🛠 Data Preprocessing
df['Year'] = pd.to_numeric(df['Year'], errors='coerce')
df["Trade Balance"] = df["India_Exports"] - df["India_Imports"]
df["Total Trade"] = df["India_Exports"] + df["India_Imports"]
# 🔥 1. India's Exports & Imports Over Time
plt.figure(figsize=(12, 6))
sns.lineplot(x="Year", y="India_Exports", data=df, label="Exports", marker="o", color="blue")
sns.lineplot(x="Year", y="India_Imports", data=df, label="Imports", marker="s", color="red")
plt.title("India's Exports & Imports (1948-2023)")
plt.xlabel("Year")
plt.ylabel("USD Billion")
plt.legend()
plt.grid(True)
plt.show()
```
## 📸 Generated Visualizations
### 1. Export & Import Growth Trend (2013-2023)
.png)
### 2. India's Imports & Exports Trend (1948-2023)
.png)
### 3. India's Trade Breakdown 2023
### 4. India's Share in Global Trade over Time
### 5. Top 10 Countries with Highest Trade Deficit
### 6. India's Position in Trade 2023
### 7. Trade Deficit Comparison between India and China (2023)
---
## 🔍 Section C : AI-Generated Reports
### 📄 1. Detailed Insights, Observations, and Recommendations on India's Trade Performance (2023)
📌 **Comprehensive analysis** covering key insights, trends, and expert recommendations for India's trade performance in 2023.
📂 **[View Report](https://github.com/pradip-data/World-Merchandise-Trade/blob/4ab61b1a611682941040f6f859c2f8a83a4d19aa/AI%20Generated%20Insights%20%26%20Recommendation/Detailed%20Insights%2C%20Observations%2C%20and%20Recommendations%20on%20India%E2%80%99s%20Trade%20Performance%20(2023).pdf)**
---
### 📄 2. India's Product-wise Trade Performance (1948-2023)
📌 **In-depth report** analyzing India's product-wise trade trends from 1948 to 2023, highlighting key patterns and growth opportunities.
📂 **[View Report](https://github.com/pradip-data/World-Merchandise-Trade/blob/8ba22ef6284438ed8727f88f5664873bc7a6b704/AI%20Generated%20Insights%20%26%20Recommendation/Insights-India's%20Product-wise%20Trade%20Performance%20(1948-2023)%20detailed.pdf)**
---
# 🌍 India's Trade Performance Analysis (2023) 🚀
## 📊 Insights: India's Trade Performance in 2023
- **Exports:** 💰 $431,574 Million USD
- **India's Export Percentage:** 🌎 1.81%
- **Export Rank:** 📈 17
- **Imports:** 💰 $672,231 Million USD
- **India's Import Percentage:** 🌍 2.77%
- **Import Rank:** 📉 8
- **Total Trade:** 💰 $1,103,805 Million USD
- **India's Total Trade Percentage:** 🌏 2.3%
- **Trade Rank:** 📊 14
- **Trade Deficit:** ❌ $240,657 Million USD
India remains one of the largest players in global trade. In 2023, India's exports crossed **$431,574 million**, placing it among the **top exporters** worldwide. However, its **imports outpaced exports**, leading to a **significant trade deficit**. India continues to be a major importer of **crude oil, gold, and electronic components**, while its key export sectors include **pharmaceuticals, IT services, and textiles**. The trade balance has been influenced by **global economic conditions, currency fluctuations, and demand shifts** in international markets.
---
## 🌎 Top Exporting Countries & Rankings (2023)
- 1️⃣ **China** - $3,379,255M
- 2️⃣ **United States** - $2,020,606M
- 3️⃣ **Germany** - $1,718,251M
- 4️⃣ **Netherlands** - $936,392M
- 5️⃣ **Japan** - $717,261M
- 6️⃣ **Italy** - $676,993M
- 7️⃣ **France** - $648,569M
- 8️⃣ **South Korea** - $632,226M
- 9️⃣ **Mexico** - $593,005M
- 🔟 **Hong Kong** - $573,871M
---
## 🌍 Top Importing Countries & Rankings (2023)
- 1️⃣ **United States** - $3,172,476M
- 2️⃣ **China** - $2,556,565M
- 3️⃣ **Germany** - $1,476,656M
- 4️⃣ **Netherlands** - $842,331M
- 5️⃣ **United Kingdom** - $791,523M
- 6️⃣ **France** - $786,158M
- 7️⃣ **Japan** - $785,796M
- 8️⃣ **India** - $672,231M
- 9️⃣ **Hong Kong** - $653,696M
- 🔟 **South Korea** - $642,572M
---
## 💰 Countries with the Highest Trade Surpluses (2023)
🔹 **China** - $822,690M
🔹 **Germany** - $241,595M
🔹 **Russia** - $120,925M
🔹 **Saudi Arabia** - $113,078M
🔹 **Netherlands** - $94,061M
---
## 🔴 Countries with the Highest Trade Deficits (2023)
❌ **United States** - $1,151,870M
❌ **United Kingdom** - $270,483M
❌ **India** - $240,657M
❌ **France** - $137,589M
❌ **Türkiye** - $106,327M
---
## ⚠️ Key Challenges Identified
- 1️⃣ **High Import Dependency** 🏭: India imports more than it exports in key categories like **fuels, machinery, and pharmaceuticals**, leading to a trade imbalance.
- 2️⃣ **Weak Export Competitiveness** 📉: India's **export share (1.81%)** is much lower than its economic size, indicating **low global competitiveness**.
- 3️⃣ **Sector-Specific Deficits** 🏥: Deficits in **pharmaceuticals and food sectors** suggest a **need for domestic production growth and export incentives**.
- 4️⃣ **Limited Market Penetration** 🌎: India relies **heavily on traditional export markets**, limiting its trade reach.
---
## 🎯 Strategic Recommendations & Policy Suggestions
### A. 🚀 Boosting Exports
✅ **Expand High-Value Manufacturing** 🔧
- Encourage **semiconductor, AI, and high-tech industries**
- Invest in **automobile and electronics manufacturing**
✅ **Strengthen Trade Agreements** 🤝
- Negotiate **preferential trade deals** with **Africa, Latin America, and Southeast Asia**
✅ **Enhance Export Incentives** 📈
- Introduce **tax benefits for export-driven industries**
### B. 📉 Reducing Import Dependence
✅ **Increase Domestic Production in Deficit Sectors** 🏭
- Expand **pharmaceutical manufacturing** to reduce **$17.9B deficit**
- Boost **agriculture and textile production** to cut food & clothing imports
✅ **Invest in Renewable Energy** ☀️
- Reduce **oil import dependency ($220.6B)** by investing in **solar, wind, and green hydrogen**
### C. 🚢 Strengthening Trade Infrastructure
✅ **Improve Logistics & Ports** ⚓
- Reduce **trade costs and shipment delays** to make exports more competitive
✅ **Ease Business Regulations** 📜
- Simplify **tax laws and streamline customs processes** for exporters
### D. 🌏 Diversifying Export Markets
✅ **Expand Beyond Traditional Markets** 🌍
- Strengthen trade with **Africa, Middle East, and Latin America**
- Reduce **over-reliance on US and European markets**
---
## 🔮 Final Outlook
India has the **potential to become a major global trade powerhouse** but must address **its trade deficit, boost exports, and reduce import dependence**. By implementing **strategic manufacturing policies, improving infrastructure, and diversifying export markets**, India can move **up in global trade rankings** and achieve a **more balanced trade profile** in the coming years.
### 🎯 Key Focus Areas for 2024 & Beyond
- ✅ Strengthen **high-value manufacturing exports**
- ✅ Reduce **fuel & machinery import dependency**
- ✅ Improve **trade policies and agreements**
- ✅ Expand **global market reach beyond traditional partners**
- ✅ Invest in **logistics and supply chain efficiency** 🚢
---
### 📊 BigQuery Analysis & Python Visualizations
📌 **BigQuery SQL Code & Execution Screenshots**
📌 **Python Code for Trade Analysis & Data Visualization**
📌 **ChatGPT AI Report Generation & Insights**
## 🏆 Final Thoughts
India has the potential to become a **major global trade powerhouse** but must address:
📉 **Trade Deficit Challenges** – Reduce reliance on imports.
🚀 **Boost Export Competitiveness** – Focus on high-value industries.
🌎 **Expand Market Reach** – Diversify beyond traditional partners.
By implementing **strategic policies**, **investing in infrastructure**, and **expanding global trade agreements**, India can significantly improve its trade rankings and achieve a **balanced trade profile** in the coming years.
---
🔗 Author & Contributions
👤 Your Name - Mangroliya Pradip
📩 For inquiries, reach out at: pradipias2023@gmail.com
---