Analyze crime trends using 2020-present real-world data. Clean, visualize patterns, correlations, and economic influences. Predict future trends and present insights in a comprehensive report. Delve into the realm of crime data analysis!

The crime dataset used in this project is available at https://catalog.data.gov/dataset/crime-data-from-2020-to-present

Tasks:

1. Data Acquisition: Download the dataset from the provided link. Load the dataset into your preferred data analysis tool.
2. Data Inspection: Display the first few rows of the dataset. Check the data types of each column. Review column names and descriptions if available.
3. Data Cleaning: Identify and handle missing data appropriately. Check for and remove duplicate rows. Convert data types if needed (e.g., dates to date format, numerical values to appropriate numeric types). Deal with outliers if relevant to your analysis. Standardize or normalize numerical data as necessary. Encode categorical data if present.
4. Exploratory Data Analysis (EDA): Visualize overall crime trends from 2020 to the present year. Analyze and visualize seasonal patterns in crime data. Identify the most common type of crime and its trends over time. Investigate notable differences in crime rates between regions or cities. Explore correlations between economic factors (if available) and crime rates. Analyze the relationship between the day of the week and the frequency of certain types of crimes. Investigate any impact of major events or policy changes on crime rates.