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sum() and count() | Analyzing the Data
Pandas First Steps
course content

Course Content

Pandas First Steps

Pandas First Steps

1. The Very First Steps
2. Reading Files in Pandas
3. Analyzing the Data

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:

  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.

Task

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
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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:

  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.

Task

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
toggle bottom row

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:

  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.

Task

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?

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:

  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.

Section 3. Chapter 15
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