Tabular data with Pandas DataFrames

Pandas builds on NumPy to provide DataFrames, two-dimensional labeled tables. You can load data from CSV files, filter rows, select columns, and compute aggregates with concise syntax.

How it reads

• pd.DataFrame(data) creates a table from a dictionary of columns
• df[df['distance_ly'] < 100] filters rows where the condition is True
• .idxmin() finds the index of the minimum value in a column

Cloud tip: Use df.info() to see column types and missing value counts, and df.describe() for statistical summaries of every numeric column.