Bangladesh rape case dataset

The \"Bangladesh Rape Cases Data\" dataset contains detailed information on rape cases reported in various districts of Bangladesh. This dataset is valuable for analyzing trends, patterns, and regional distributions of reported rape cases over a decade. It can be utilized by researchers, policymakers, and social scientists to study and address the issue of rape in Bangladesh. Total Sample Size: This dataset comprises a total of 2,813 rows, each representing an individual case reported in various districts across Bangladesh. Data Description: headline: Type: String Description: The headline of the news article reporting the rape case. It provides a brief summary of the incident. district-tag: Type: String Description: The district where the incident occurred. This helps in identifying the geographical distribution of the cases. division-tag: Type: String Description: The division of Bangladesh to which the district belongs. This is useful for broader regional analysis. subdistrict-tag: Type: String Description: The specific subdistrict or locality within the district where the incident occurred. This column may contain missing values if the subdistrict is not specified. id: Type: String (UUID format) Description: A unique identifier for each news article, ensuring that each entry can be distinctly referenced. url: Type: String Description: The web link to the original news article, allowing users to access the full report for more detailed information. last-published-at: Type: DateTime Description: The date and time when the news article was last published, helping to understand the timeline of the reported cases. offset: Type: Integer Description: An offset value for the article, potentially indicating its position in a larger dataset or the order of processing. content: Type: String Description: The main content of the news article, providing detailed information about the incident. Temporal Coverage: Minimum Date: February 22, 2013 Maximum Date: April 10, 2023 The dataset spans over a decade, allowing for a comprehensive temporal analysis of the reported cases. Potential Uses: Trend Analysis: Analyze how the frequency of reported cases changes over time. Geographical Analysis: Identify regions with higher or lower reporting rates. Content Analysis: Examine the language and details provided in the headlines and content to understand the nature of reporting. Correlation Studies: Investigate possible correlations between reported cases and other socio-economic factors. Data Quality and Considerations: Missing Values: Some columns, such as subdistrict-tag, may contain missing values where specific information was not provided. Data Source: The data is sourced from news articles, so it may be influenced by reporting biases and the availability of news coverage.