Dhaka Weather Analysis (1953–2016)
Sadidul Kabir
0
Data Visualizer
Data Analyst
Statistician
pandas
Python
seaborn
Goal:
The data set we will use for data analysis is Dhaka weather data from 1953 to 2016.
Description:
The project focused on analyzing a dataset of weather data that was collected from the Bangladesh Meteorological Department. The dataset included YEAR, Month, MaxTemp, MinTemp, RelativeHumidity, Rainfall, and other relevant information. The project involved loading the data, cleaning and preprocessing it, performing exploratory data analysis (EDA), analyzing the correlation, and implementing Pearson’s correlation statistical analysis.
Skills:
Data cleaning, data analysis, correlation matrices, statistical analysis, data visualization, and finding insights.
Technology:
Python, Pandas, NumPy, Seaborn, Matplotlib.
Results:
Jun, July and August are most Rainy Months
April, May, Jun and July are most Max Temperature Months
December, January and February are most Min Temperature Months
Jun, July and August has Highly Relative Humidity
Rainfall & Humidity are highly Correlated
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This project focused on analyzing a dataset of weather data that was collected from the Bangladesh Meteorological Department.
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Tags
Data Visualizer
Data Analyst
Statistician
pandas
Python
seaborn
Sadidul Kabir
Data Professional
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