csv-analyzer

To analyze CSV files for basic statistics and data types, this skill estimates per-column types and reports missing values. It generates a complete JSON summary including row counts, column counts, encoding, and file size for quick data profiling.

Detect missing values and profile data across different CSV encodings using built-in encoding detection. This skill processes files of various sizes, identifies per-column missing values, and delivers a structured metadata summary for validation.

Validating CSV structure and estimating column data types is achieved through deterministic data profiling. This skill analyzes the file to provide row counts, column counts, and per-column type estimation, ensuring quick visibility into your dataset.

Pandas supports CSV data validation and profiling within this skill as a required dependency. It leverages pandas to estimate per-column data types, detect missing values, and calculate basic statistics for numeric columns across various file sizes.

Analyzing large CSV files of various sizes and encodings is supported by this skill. It utilizes chardet for encoding detection and applies deterministic analysis to summarize row counts, column types, and basic statistics across diverse datasets.

CSV analysis might not detect the correct file encoding if the dataset uses unusual character sets. This skill relies on chardet for encoding detection, which handles various encodings, but highly irregular files may require preliminary manual inspection.