sum() and count() | Analyzing the Data

Course Content

Pandas First Steps

## sum() and count()

Pandas offers the `count()` function, 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()` function. 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:

Given the dataframe `audi_cars`:

1. Determine the count of non-null cells in each column.
2. Compute the total price (using the `price` column) for all cars in the DataFrame.

Everything was clear?

Section 3. Chapter 15

Course Content

Pandas First Steps

## sum() and count()

Pandas offers the `count()` function, 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()` function. 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:

Given the dataframe `audi_cars`:
2. Compute the total price (using the `price` column) for all cars in the DataFrame.