The average for 2018 based on 86 countries was 24.26 students per teacher. The highest value was in Rwanda: 59.51 students per teacher and the lowest value was in San Marino: 6.93 students per teacher. The indicator is available from 1970 to 2019. Below is a chart for all countries where data are available.

The average for 2018 based on 23 countries was 37.18 students per teacher. The highest value was in Rwanda: 59.51 students per teacher and the lowest value was in the Seychelles: 14.49 students per teacher. The indicator is available from 1970 to 2019. Below is a chart for all countries where data are available.

Kaggle Dataset Description

Title: Pupil-Teacher Ratio in Primary Education
Subtitle: Analyzing global trends in educational quality through pupil-teacher ratios.

Detailed Description:
This dataset contains data on the pupil-teacher ratio in primary education, which measures the average number of pupils per teacher. It is a critical indicator of educational quality and infrastructure. Sourced from the World Bank, this dataset spans several decades and countries, offering insights into the adequacy of teaching resources worldwide.

Key Highlights: - Annual data for countries worldwide. - Metric: Number of pupils per teacher in primary education. - Use cases: Analyze trends, compare regional disparities, and study correlations with literacy rates, GDP, and enrollment rates.

4. Exploratory Data Analysis (EDA)

Notebook Ideas

1. Data Cleaning:

   • Handle missing or inconsistent values.
   • Normalize data to compare across countries with varying education systems.
   • Aggregate data by regions or income levels for a comprehensive analysis.

2. Visualizations:

   • Line Graph: Trends in pupil-teacher ratios over time for selected countries.
   • Heatmap: Regional disparities in pupil-teacher ratios by year.
   • Scatterplot: Correlation between pupil-teacher ratios and literacy rates or GDP.
   • Bar Chart: Top and bottom countries by pupil-teacher ratios for a given year.

3. Descriptive Analysis:

   • Highlight regions with the lowest and highest pupil-teacher ratios.
   • Analyze changes over time in countries with significant improvements.
   • Explore patterns in regions with higher teacher availability.

5. Predictive Analysis (Optional)

• Use time-series forecasting (e.g., ARIMA or Prophet) to predict future trends in pupil-teacher ratios.
• Apply clustering algorithms to group countries with similar trends in educational infrastructure.

6. Kaggle Notebook

Create a Kaggle notebook with: 1. Data Cleaning: Handle missing values or inconsistencies. 2. EDA: Include compelling visualizations like heatmaps, scatterplots, and line charts. 3. Insights: Highlight findings, such as regions with the best and worst pupil-teacher ratios or trends over time. 4. Optional Predictive Modeling: Use regression or time-series models to forecast future ratios.

7. Call to Action

For GitHub:

• Share the GitHub repository link on LinkedIn, Twitter, and forums like Reddit (e.g., r/datascience).
• Invite collaboration:
  • "Fork this repository and contribute by adding insights or new visualizations!"

GitHub Link: https://github.com/AmsalAli/Pupil_Teacher_Ratio_Trends

For Kaggle:

• Encourage upvotes:
  • "If this dataset helps you, please upvote it to make it more visible for others!"
• Engage users with questions:
  • "Which regions have made the most progress in reducing pupil-teacher ratios?"
  • "How do pupil-teacher ratios affect literacy and enrollment rates?"

Kaggle Link: https://www.kaggle.com/datasets/yourusername/pupil-teacher-ratio

8. LinkedIn Post

Post Title:
📚 Global Trends in Pupil-Teacher Ratios in Primary Education 🌍

Post Body:
Excited to share my latest dataset on pupil-teacher ratios in primary education, sourced from the World Bank. This dataset measures the average number of pupils per teacher, offering critical insights into global educational quality.

📂 Explore the Dataset:
- GitHub Repository: https://github.com/AmsalAli/Pupil_Teacher_Ratio_Trends
- Kaggle Dataset: https://www.kaggle.com/datasets/yourusername/pupil-teacher-ratio

Why It Matters:

The pupil-teacher ratio is a key indicator of educational quality and infrastructure. This dataset is ideal for:
- Trend Analysis: Study changes in pupil-teacher ratios across decades.
- Regional Comparisons: Identify disparities in teaching resources globally.
- Correlations: Explore the impact of pupil-teacher ratios on literacy and enrollment rates.

📈 Get Involved:
- Use this dataset for your analyses and visualizations.
- Share your insights and findings.
- Upvote on Kaggle to help others discover it!

❓ What trends or insights can you uncover from this data?
- Which countries have the most favorable pupil-teacher ratios?
- What factors drive disparities in teacher availability globally?

Let me know your thoughts, and feel free to share this resource with others! 🌟

DataScienc...

The average for 2018 based on 13 countries was 41.92 students per teacher. The highest value was in Rwanda: 59.51 students per teacher and the lowest value was in North Korea: 20.3 students per teacher. The indicator is available from 1970 to 2019. Below is a chart for all countries where data are available.

The United Kingdom had an average of **** students per teacher at middle schools in 2019, the highest among the provided countries. By comparison, Iceland had just **** students for every member of staff in this year, the lowest ratio among the displayed countries.

In 2022, there was an average of **** students for every member of academic staff in the French primary schools, the highest rate among the provided countries. By contrast Iceland had less than **** students for every member of staff at primary education, the lowest among the countries displayed here.