So far, we have covered standard CSV format, its variations, and common configurations in Python's csv module.
Now you'd understand what a standard CSV looks like, how the specification defines data boundaries and escapes special characters.
In this part, we will explore few advanced topics related to format variations and additional settings in Python's csv module.
In the last article, we explained how CSV specification defines columns and eliminates ambiguity to correctly identify delimiters and quotes. In this part, we will focus on how CSV defines row boundaries and cover how CSV parsers handles malformed data.
In previous article, we talked about how the CSV format represents tabular data, its simplicity, and its limitation on data types support. For now, our example still looks similar to regular CSV tutorials because we worked with standard, simplified data. We will dive into complex cases in future articles, and this post will focus on CSV structure: how the format accuratly defines table cells/columns.
CSV (Comma-Separated Values) files are common to anyone working with tabular data, no matter if those data are called "tables" or "spreadsheets" in conversations or your computer. If you work in information technology industry, you've likely encountered them repeatedly in class assignments, personal projects, or data-centered tasks in the workplace, from fundamental data engineering to analytics applications.
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