### Issue 1: Missing Abbreviation Scheme Explanation

**Issue**: "Unclear abbreviation scheme in README"

**Evidence**: "`state - US state 2 digit code`"

**Description**: The README file mentions a two-digit code for the US states but does not provide an explanation or reference to what these codes are or how to interpret them. This could cause confusion for users unfamiliar with the specific codes used for each state, thereby impeding the understanding and analysis of the dataset. An abbreviation scheme or a reference link should be included to clarify this information.

### Now let's analyze the CSV file for any issues related to missing information or other problems, focusing on the hint provided.### Issue 2: Missing Information on Probable Cases and Pending Test Results

**Issue**: "Missing explanation for 'NaN' values in probableCases and pending columns"

**Evidence**: "`probableCases` and `pending` columns contain NaN values"

**Description**: The CSV file contains columns labeled `probableCases` and `pending`, both of which have numerous NaN (not a number) entries. The README or any supplementary documentation does not explain the meaning or reasoning behind these NaN values. Is a NaN value an indication of unavailable data, or does it signify that the category is not applicable to the corresponding state for that day? An explicit clarification on how to interpret these NaN values is crucial for accurate data analysis.

### Issue 3: Unclear Total Test Results Source

**Issue**: "Unclear definition of 'totalTestResultsSource' column"

**Evidence**: "`totalTestResultsSource` column with mixed value types like 'totalTestsViral' and 'totalTestsPeopleViral'"

**Description**: The dataset includes a `totalTestResultsSource` column, which appears to have mixed types of data sources (e.g., 'totalTestsViral' and 'totalTestsPeopleViral'). The README file does not provide definitions or descriptions for these sources. Without understanding the distinction between these sources, users may misinterpret the data or draw incorrect conclusions. It would be beneficial to include a detailed explanation of what each data source means and how they differ.

These issues were identified by examining the README file and the CSV dataset, focusing on the hint provided regarding missing information and unclear abbreviation scheme.