### Install pandasql

Source: https://github.com/yhat/pandasql/blob/master/README.rst

Install the pandasql library using pip.

```bash
pip install -U pandasql
```

--------------------------------

### Joining DataFrames with pandasql

Source: https://github.com/yhat/pandasql/blob/master/README.md

Illustrates how to perform SQL JOIN operations between pandas DataFrames using pandasql. This example joins 'meat' and 'births' DataFrames on their 'date' column.

```python
q = """SELECT
        m.date, m.beef, b.births
     FROM
        meats m
     INNER JOIN
        births b
           ON m.date = b.date;"""
joined = pyqldf(q)
print joined.head()
```

--------------------------------

### SQL Aggregation with pandasql

Source: https://github.com/yhat/pandasql/blob/master/README.md

Shows how to use SQL aggregation functions like SUM and GROUP BY with pandasql. This example calculates the total beef consumption per year from the 'meat' DataFrame.

```python
q = "select
           strftime('%Y', date) as year
           , SUM(beef) as beef_total
           FROM
              meat
           GROUP BY
              year;"
print pysqldf(q).head()
```

--------------------------------

### Query DataFrame with PandaSQL Class

Source: https://github.com/yhat/pandasql/blob/master/README.rst

Demonstrates querying a pandas DataFrame using the PandaSQL class. Load data, create a PandaSQL instance, and execute a SQL query to select the first 10 rows.

```python
from pandasql import PandaSQL, load_meat, load_births
meat = load_meat()
births = load_births()
pdsql = PandaSQL()
print pdsql("SELECT * FROM meat LIMIT 10;").head()
```

--------------------------------

### Basic DataFrame Query with pandasql

Source: https://github.com/yhat/pandasql/blob/master/README.md

Demonstrates how to query a pandas DataFrame using SQL syntax with the sqldf function. A helper function `pysqldf` is defined for convenience. This snippet shows selecting and limiting results from the 'meat' DataFrame.

```python
from pandasql import sqldf, load_meat, load_births
pysqldf = lambda q: sqldf(q, globals())
meat = load_meat()
births = load_births()
print pysqldf("SELECT * FROM meat LIMIT 10;").head()
```

--------------------------------

### Aggregate Data with PandaSQL

Source: https://github.com/yhat/pandasql/blob/master/README.rst

Calculate the total beef consumption per year by grouping data from the 'meat' DataFrame using a SQL query executed by PandaSQL.

```python
q = "select
               strftime('%Y', date) as year
               , SUM(beef) as beef_total
               FROM
                  meat
               GROUP BY
                  year;"
print pdsql(q).head()
```

--------------------------------

### Join DataFrames with PandaSQL

Source: https://github.com/yhat/pandasql/blob/master/README.rst

Perform an inner join between two pandas DataFrames ('meats' and 'births') using a SQL query executed by PandaSQL.

```python
q = """SELECT
            m.date, m.beef, b.births
         FROM
            meats m
         INNER JOIN
            births b
               ON m.date = b.date;"""
joined = pdsql(q)
print joined.head()
```

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