Weather-Analysis-Project

Welcome to my Weather Analysis Project repository! This project is focused on analyzing a time series dataset containing hourly weather conditions at a specific location. The dataset includes information about temperature, dew point temperature, relative humidity, wind speed, visibility, pressure, and conditions.

Dataset

The dataset used for this project is available in CSV format and is included in the data directory of this repository. The columns in the dataset include:

• Temperature
• Dew Point Temperature
• Relative Humidity
• Wind Speed
• Visibility
• Pressure
• Conditions

Functions and Insights

In this project, I've implemented various functions to analyze the dataset using the Pandas DataFrame library. Here are some of the insights I've derived from the data:

1. Unique Wind Speed Values: Found all the unique 'Wind Speed' values in the data.
2. Clear Weather Count: Determined the number of times when the 'Weather is exactly Clear'.
3. Wind Speed of 4 km/h Count: Found the number of times when the 'Wind Speed was exactly 4 km/h'.
4. Null Values: Identified all the Null Values in the data.
5. Column Renaming: Renamed the column name 'Weather' of the DataFrame to 'Weather Condition'.
6. Mean Visibility: Calculated the mean 'Visibility'.
7. Standard Deviation of Pressure: Calculated the Standard Deviation of 'Pressure' in this data.
8. Variance of Relative Humidity: Found the Variance of 'Relative Humidity' in this data.
9. Instances of Snow: Identified all instances when 'Snow' was recorded.
10. Wind Speed and Visibility Criteria: Found all instances when 'Wind Speed is above 24' and 'Visibility is 25'.
11. Mean Values by Weather Condition: Calculated the Mean value of each column against each 'Weather Condition'.
12. Min and Max Values by Weather Condition: Found the Minimum and Maximum value of each column against each 'Weather Condition'.
13. Records with Fog: Showed all the Records where Weather Condition is 'Fog'.
14. Clear Weather or Visibility Criteria: Found all instances when either 'Weather is Clear' or 'Visibility is above 40'.
15. Complex Criteria: Identified instances when:
    • A. 'Weather is Clear' and 'Relative Humidity is greater than 50', OR
    • B. 'Visibility is above 40'.

Files and Directories

• Weather Data.csv:The CSV file of the weather dataset.
• Data Analysis Project-1.ipynb: Jupyter Notebook containing the analysis code.
• README.md: You're currently reading it!

Getting Started

To explore this project on your local machine, follow these steps:

1. Clone this repository using: git clone https://github.com/SakshiJSanghavi/Weather-Analysis-Project.git
2. Open and run the Data Analysis Project-1.ipynb notebook to see the data analysis and insights.

Contributions

Contributions to this project are welcome! If you have any suggestions, improvements, or bug fixes, feel free to create an issue or submit a pull request.

Contact

If you have any questions or want to connect, you can reach me at sakshi.sanghavi1016@gmail.com.

Happy exploring and analyzing the weather data!