2 Working with Data and Data Types Free Online FlashCards

In a tabular dataset, what do rows and columns represent?

Rows represent observations, and columns represent variables.

What is a pandas DataFrame?

A DataFrame is a two-dimensional table whose columns can have different data types.

What does pandas `read_csv()` do?

`read_csv()` loads a CSV file into a DataFrame.

What does a DataFrame’s `shape` tell you?

`shape` reports the number of rows and columns.

Why should a customer ID usually not be treated as a quantity?

A customer ID is an identifier, not a quantity; averaging IDs has no useful meaning.

What does a missing value mean, and what is it not automatically equivalent to?

A missing value means an observation is unavailable or unrecorded. It is not automatically equivalent to zero, an empty string, or “none.”

How can you spot inconsistent category values?

Compare distinct values with expected categories; capitalization differences such as `North` and `north` may indicate inconsistency.

What should you do before converting a text column to dates or numbers?

Check formats and decide how to handle values that do not convert before changing types; otherwise, valid information may be lost or misrepresented.

What is a pandas Series in relation to a DataFrame?

A Series is a labeled one-dimensional structure; each DataFrame column behaves like one.

How can you preview the first rows of a DataFrame?

`head()` previews the first rows of a DataFrame.

What does pandas `info()` help inspect?

`info()` summarizes column types and non-missing counts.

What does a DataFrame’s `dtypes` attribute show?

`dtypes` shows the data type of each column.