How to Rewrite SQL Queries in Pandas

How to Rewrite SQL Queries in Pandas

Learn how to write your SQL queries in Python's Pandas syntax. This article attempts to provide a mapping between common operations in SQL and their counterpart in Pandas using a fictional housing dataset.

If you’re reading this, you probably know some SQL and are aware of some of its building blocks (in order of operation):

  1. from (including joins)
  2. where
  3. group by
  4. having
  5. select
  6. order by
  7. limit

But now you’re doing some analysis in Pandas and you need to be able to query your dataframe much like you usually do in SQL. This article attempts to provide a mapping between common operations in SQL and their counterpart in Pandas using a fictional housing dataset.

Select, order by, and limit

Say you want to select all columns in your dataset and limit the number of rows coming back. In SQL,

select *
from housing
limit 10

In Pandas,

housing_df.head(10)

Want to order by number of bedrooms? In SQL,

select *
from housing
order by num_bedrooms
limit 10

In Pandas,

housing_df.sort_values(by=['num_bedrooms']).head(10)

Just want to select a few columns? In SQL,

select num_bedrooms, price
from housing

In Pandas,

housing_df[['num_bedrooms', 'price']]

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