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View All on GitHubAI Summary: Clean a dataset by removing null values and duplicate rows using pandas in Python. The task involves using `df.isnull().sum()` to identify nulls, and then applying `dropna()` and `drop_duplicates()` methods. The shape of the dataset before and after cleaning should be printed to demonstrate the changes.
AI Summary: Create a histogram visualization of the 'Runs_Scored' column from the provided dataset using Matplotlib or Seaborn. The histogram should be properly labeled and titled, and a brief explanation of what the histogram reveals about the data's distribution should be included in the code comments or a markdown cell.
AI Summary: Generate a correlation matrix heatmap for numerical features in a dataset using pandas and seaborn in a Jupyter Notebook. Save the heatmap as 'heatmap.png'. The heatmap should include labels, title, and a color bar.