Course Content

Pandas First Steps

## Pandas First Steps

# sum() and count()

Pandas offers the `count()`

method, which counts all non-null cells (neither None nor np.NaN) for each column. Consider the following example:

To find the **count** of non-null values in a specific column, use:

Pandas also provides the `sum()`

method. This function calculates the sum of values for each column, but it only works with numeric columns. Check out the following example:

To find the sum of values in a particular column:

Task

Given the dataframe `audi_cars`

:

- Determine the count of non-null cells in each column.
- Compute the total price (using the
`price`

column) for all cars in the DataFrame.

Task

Given the dataframe `audi_cars`

:

- Determine the count of non-null cells in each column.
- Compute the total price (using the
`price`

column) for all cars in the DataFrame.

Everything was clear?

# sum() and count()

Pandas offers the `count()`

method, which counts all non-null cells (neither None nor np.NaN) for each column. Consider the following example:

To find the **count** of non-null values in a specific column, use:

Pandas also provides the `sum()`

method. This function calculates the sum of values for each column, but it only works with numeric columns. Check out the following example:

To find the sum of values in a particular column:

Task

Given the dataframe `audi_cars`

:

- Determine the count of non-null cells in each column.
- Compute the total price (using the
`price`

column) for all cars in the DataFrame.

Task

Given the dataframe `audi_cars`

:

- Determine the count of non-null cells in each column.
- Compute the total price (using the
`price`

column) for all cars in the DataFrame.

Everything was clear?

# sum() and count()

Pandas offers the `count()`

method, which counts all non-null cells (neither None nor np.NaN) for each column. Consider the following example:

To find the **count** of non-null values in a specific column, use:

Pandas also provides the `sum()`

method. This function calculates the sum of values for each column, but it only works with numeric columns. Check out the following example:

To find the sum of values in a particular column:

Task

Given the dataframe `audi_cars`

:

- Determine the count of non-null cells in each column.
- Compute the total price (using the
`price`

column) for all cars in the DataFrame.

Task

Given the dataframe `audi_cars`

:

- Determine the count of non-null cells in each column.
- Compute the total price (using the
`price`

column) for all cars in the DataFrame.

Everything was clear?

`count()`

method, which counts all non-null cells (neither None nor np.NaN) for each column. Consider the following example:

To find the **count** of non-null values in a specific column, use:

`sum()`

method. This function calculates the sum of values for each column, but it only works with numeric columns. Check out the following example:

To find the sum of values in a particular column:

Task

Given the dataframe `audi_cars`

:

- Determine the count of non-null cells in each column.
- Compute the total price (using the
`price`

column) for all cars in the DataFrame.