Iran Airlines Data Analysis with Tableau

Project Overview

The Tehran Airlines dataset includes metrics on air quality and meteorological factors across multiple stations, with key indicators like PM2.5, CO, and NO2 levels, as well as temperature extremes, wind patterns, and aerosol optical depth measurements. This project uses Tableau's visualization tools to create engaging dashboards and an interactive story that brings forward critical trends and actionable insights.

Dataset

• Data Source: Tehran Airlines Dataset
• Data Description: The dataset contains air quality and meteorological data across multiple stations with the following columns:

Column Name	Description	Data Type
date	Date of data recording	Object
pm25	PM2.5 concentration	Float64
no2	NO2 concentration	Float64
co	CO concentration	Float64
timeframe	Timeframe for recording	Float64
min, max	Min & Max readings for the period	Float64
stage1, stage2, stage3	Pollution stages	Float64
station_id_x, station_id_y, station_id	Unique station IDs	Float64, Int64
station_name	Name of the station	Object
lat_x, lon, lat_y, long	Latitude and longitude	Float64
station_elevation	Elevation of the station	Float64
vvmin, ffm, tmax, tmin, tm	Weather parameters	Float64
rrr24, nm, umax, umin, um, sshn	Additional weather metrics	Float64
x_utm, y_utm	UTM coordinates	Float64
aod_1 to aod_9	Aerosol Optical Depth measurements	Float64
month_period	Monthly period indicator	Object

Sheets Overview

Sheet 1: Temperature Analysis

• Columns: Month (Month Period)
• Rows: SUM(Tmax), SUM(Tmin)
• Purpose: Visualizes monthly trends in maximum and minimum temperatures.

Sheet 2: Pollution by Station

• Columns: Station Name
• Rows: SUM(Pm25), SUM(Co)
• Purpose: Analyzes pollution levels per station based on PM2.5 and CO concentrations.

Sheet 3: Pollution Stages by Month and Station

• Columns: Month (Month Period)
• Rows: Station Name, AVG(Stage1), AVG(Stage2)
• Purpose: Tracks average pollution stages across stations by month.

Sheet 4: Aerosol Optical Depth Analysis

• Columns: Station Name
• Rows: SUM(Aod1) through SUM(Aod9)
• Purpose: Examines AOD distribution across stations to understand particulate matter trends.

Sheet 5: Yearly Wind Speed Trends

• Columns: YEAR(Month Period)
• Rows: SUM(Umax), SUM(Umin)
• Purpose: Displays yearly variations in maximum and minimum wind speeds.

Sheet 6: Average Wind Speed by Station

• Columns: Station Id
• Rows: AVG(Umax), AVG(Umin)
• Purpose: Compares average wind speeds across stations.

Sheet 7: Station Trends by Month

• Columns: Month (Month Period)
• Rows: Station Name
• Purpose: Observes station data trends over monthly periods.

Sheet 8: Elevation and NO2 Concentration

• Columns: Station Name
• Rows: SUM(Station Elevation), SUM(No2)
• Purpose: Correlates station elevation with NO2 concentration levels.

Sheet 9: Humidity and Precipitation by Station

• Columns: Station Name
• Rows: SUM(Ffm), Max(Rrr24)
• Purpose: Shows total humidity and maximum precipitation per station.

Story Section

The story contains three dashboards, each emphasizing distinct aspects of the data:

1. Dashboard 1: Monthly temperature averages and pollutant levels, highlighting seasonal patterns.

2. Dashboard 2: Aerosol concentrations and wind speed trends across stations by year.

3. Dashboard 3: Station elevation effects on NO2 levels and wind speed metrics.

Files

• IranAirlinesAnalysis.twb: The Tableau workbook with all sheets, dashboards, and story.
• Report.pdf: A report summarizing key insights, findings, and recommendations.

Contact

For questions or suggestions, please reach out to [laibamazhar.000@gmail.com].