Data Analysis with weather data
Budget: $30 – $250 USD
I have the Rainfall and temperature data for last 5 years for 25 Districts in Sri lanka. I want to get below insights from that data
A. Climate Trends
• Temperature Trends:
o Analyze average monthly and yearly temperatures by district to identify warming or cooling trends.
o Compare temperature fluctuations across districts or regions.
• Rainfall Trends:
o Determine seasonal rainfall patterns (e.g., monsoon periods).
o Compare districts with consistent high or low rainfall.
• Extreme Weather Events:
o Identify outliers in data (e.g., droughts, floods) and their frequency.
o Correlate with disaster response data if available.
B. Regional Comparisons
• Compare coastal and inland districts for variations in weather.
• Analyze regions most affected by specific weather patterns, like heavy monsoons or heatwaves.
C. Seasonal Analysis
• Map out clear seasonal cycles and their deviations over the years.
• Identify seasons that are shifting in timing or intensity.
D. Climate Change Indicators
• Detect long-term changes in temperature, rainfall, and extreme weather events.
• Compare trends with global climate models to assess alignment.
E. Visualizations
Use graphs and maps for impactful insights:
• Heatmaps: Show temperature or rainfall distribution by district.
• Time Series: Highlight trends over the five years.
• Bar Graphs/Box Plots: Compare weather patterns across districts.
• GIS Mapping: Combine geospatial and weather data for interactive district-level insights.
Output should be provide in Power BI
A. Climate Trends
• Temperature Trends:
o Analyze average monthly and yearly temperatures by district to identify warming or cooling trends.
o Compare temperature fluctuations across districts or regions.
• Rainfall Trends:
o Determine seasonal rainfall patterns (e.g., monsoon periods).
o Compare districts with consistent high or low rainfall.
• Extreme Weather Events:
o Identify outliers in data (e.g., droughts, floods) and their frequency.
o Correlate with disaster response data if available.
B. Regional Comparisons
• Compare coastal and inland districts for variations in weather.
• Analyze regions most affected by specific weather patterns, like heavy monsoons or heatwaves.
C. Seasonal Analysis
• Map out clear seasonal cycles and their deviations over the years.
• Identify seasons that are shifting in timing or intensity.
D. Climate Change Indicators
• Detect long-term changes in temperature, rainfall, and extreme weather events.
• Compare trends with global climate models to assess alignment.
E. Visualizations
Use graphs and maps for impactful insights:
• Heatmaps: Show temperature or rainfall distribution by district.
• Time Series: Highlight trends over the five years.
• Bar Graphs/Box Plots: Compare weather patterns across districts.
• GIS Mapping: Combine geospatial and weather data for interactive district-level insights.
Output should be provide in Power BI