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5. DataFrame: Quick Inspection & Conversion

Status

Done

5. Quick Inspection & Conversion

Peek at data or convert to NumPy.

df.head(n) → Return first n rows (default 5).
df.tail(n) → Return last n rows.
df.values → Return DataFrame values as a NumPy array (legacy).
df.to_numpy() → Preferred way to convert DataFrame to NumPy array.

Quick Inspection & Conversion in Pandas DataFrames

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1. `df.head()` - Initial Data Inspection

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2. `df.tail()` - End Data Inspection

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3. `df.values` - Legacy NumPy Conversion

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4. `df.to_numpy()` - Modern NumPy Conversion

Performance & Memory Considerations

Comparison Table

Method	Speed	Memory	Type Preservation	Recommended
`head()`/`tail()`	Very Fast	Minimal	Full	✅ Always
`values`	Fast	Variable	Poor	❌ Legacy
`to_numpy()`	Fast	Controlled	Good	✅ Preferred

Best Practices

Use head()/tail() for quick inspection and debugging
Prefer to_numpy() over values for conversion
Specify dtypes when using to_numpy() for better memory usage
Handle missing values explicitly during conversion

Real-World Workflow Example

python

def data_quality_pipeline(df):
    """Professional data inspection and validation workflow"""

    # Initial inspection
    print("=== DATA QUALITY REPORT ===")
    print(f"Shape: {df.shape}")
    print("\nFirst 5 rows:")
    print(df.head())

    print("\nLast 5 rows:")
    print(df.tail())

    # Type-specific validation
    numeric_cols = df.select_dtypes(include='number')
    print(f"\nNumeric data preview ({len(numeric_cols.columns)} columns):")
    print(numeric_cols.head(3))

    # Prepare for analysis
    print("\nConverting to NumPy for statistical analysis...")
    analysis_data = numeric_cols.to_numpy(dtype='float64')
    print(f"Analysis array shape: {analysis_data.shape}")

    return analysis_data

# Execute pipeline
analysis_data = data_quality_pipeline(df)

This comprehensive guide shows how these simple methods form the foundation of professional data inspection and conversion workflows in pandas.

5. DataFrame: Quick Inspection & Conversion

5. Quick Inspection & Conversion

Quick Inspection & Conversion in Pandas DataFrames

1. df.head() - Initial Data Inspection

2. df.tail() - End Data Inspection

3. df.values - Legacy NumPy Conversion

4. df.to_numpy() - Modern NumPy Conversion

Performance & Memory Considerations

Comparison Table

Best Practices

Real-World Workflow Example

1. `df.head()` - Initial Data Inspection

2. `df.tail()` - End Data Inspection

3. `df.values` - Legacy NumPy Conversion

4. `df.to_numpy()` - Modern NumPy Conversion