Data Validation
Data validation involves checking various aspects of your dataset, such as missing values, data types, outliers, and adherence to specific rules or constraints. Validating our data helps maintain its quality and integrity, ensuring that any analyses or decisions made based on the data are robust and reliable.
Validate data in a dataframe using R
Data validation is a critical aspect of data analysis, ensuring that the data we’re working with is accurate, consistent, and reliable. In R Programming Language there are several methods and packages available to validate data, allowing us to identify and address any issues or anomalies present in our dataset.
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