1. Assignment 2: Weather
- Plot dry bulb temperature vs time using a Jupyter notebook.
2. Assignment 3: Domains
- Create a pie chart of email domains from the csv file using the url provided.
3. Assignment 5: Risk
- Write a program that simulates 1000 individual battle rounds in Risk.
- Create a full series of rounds for armies of arbitary sizes, until one side is wiped out.
4. Assignment 6: Weather Knock Airport
- Plot temperature, mean temperature each day and mean temperature each month from the csv file using the url provided.
- Plot windspeed, rolling windspeed over 24 hours, max windspeed per day and monthly mean of the daily max windspeeds.
Data Processing and analysis:
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Jupyter notebook: open source web application used for python coding in real time, text and visualisations.
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Pandas: open-source python library built on top of NumPy used for data manipulation and analysis.
- The CSV datasets were loaded into a pandas dataFrame using pd.read_csv(). The data was cleaned using methods like dropna() to remove missing values. groupby() and resample()splits data into groups and allowed aggregation of data using mean() etc.
- For time-series analysis, the pandas datetime function was used to process dates and times. pd.to_datetime() used to convert string dates into datetime objects.
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Data Visualisation: Matplotlib: python library used to create plots to display the data graphically.
- Anaconda for creating and managing Python environments
- Visual Studio Code for editing and running the code.