Final answer:
Two potential problems in the Data Cleaning/Wrangling step are missing values and inconsistent data formats.
Step-by-step explanation:
Two potential problems in the Data Cleaning/Wrangling step are missing values and inconsistent data formats.
Missing values occur when there are empty or null values in the data. This can lead to difficulties in analyzing the data or deriving meaningful insights. It is important to handle missing values appropriately, either by imputing them or excluding them from the analysis.
Inconsistent data formats refer to variations in how data is structured or represented. For example, dates may be stored in different formats (mm/dd/yyyy or dd/mm/yyyy) or numeric values may have different units (miles or kilometers). Inconsistent data formats can make it challenging to combine or compare data from different sources, and may require standardization or conversion.