PYTHON APPLIED
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.
Check your understanding
Answer all 3 to complete this lesson · +15 XP
1. What Pandas function loads a CSV file into a DataFrame?
2. How do you filter a DataFrame to rows where column 'x' is greater than 5?
3. What method provides a statistical summary of numeric columns?