SQL is way easier when you actually know what matters.
These are the core basics every beginner needs to build projects, answer real business questions, and stop feeling overwhelmed π
Master these first and everything else becomes 10x easier.
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These are the core basics every beginner needs to build projects, answer real business questions, and stop feeling overwhelmed π
Master these first and everything else becomes 10x easier.
Save this to review later β
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Working with multiple datasets? Combine them just like SQL:
# Inner join (default)
merged = pd.merge(df_sales, df_customers, on='customer_id')
# Left join
pd.merge(df_sales, df_customers, on='customer_id', how='left')
# Concatenate vertically
all_data = pd.concat([df_2023, df_2024], ignore_index=True)
# Join on index
df1.join(df2, on='date')
This wraps up our Data Manipulation Using Pandas Series.
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They donβt touch your data β they shape where your data lives.
Use CREATE, ALTER, and DROP to define and change your database structure.
π‘ Powerful, essential β and should be used with care!
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