Pandas provides powerful tools for joining DataFrames. Here’s a comprehensive guide.

Merge Types

Inner Join

import pandas as pd

df1 = pd.DataFrame({'key': ['A', 'B'], 'value1': [1, 2]})
df2 = pd.DataFrame({'key': ['B', 'C'], 'value2': [3, 4]})

result = pd.merge(df1, df2, on='key', how='inner')

Left Join

result = pd.merge(df1, df2, on='key', how='left')

Right Join

result = pd.merge(df1, df2, on='key', how='right')

Outer Join

result = pd.merge(df1, df2, on='key', how='outer')

Multiple Keys

result = pd.merge(df1, df2, on=['key1', 'key2'])

Best Practices

  1. Choose the right join type
  2. Handle missing values
  3. Use appropriate keys
  4. Check for duplicates
  5. Optimize for large datasets

Conclusion

Master Pandas joins for efficient data manipulation! 📊