Learn sum() and count() | Analyzing the Data

pandas offers the count() method, which counts all non-null cells (neither None nor NaN) for each column.

df = pd.read_csv(file.csv)
number_of_cells = df.count()

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

df = pd.read_csv(file.csv)
number_of_cells = df['name of the column'].count()

pandas also provides the sum() method. This method calculates the sum of values for each column, but it only works with numeric or boolean columns.

df = pd.read_csv(file.csv)
total = df.sum()

Since the isna() method returns a boolean DataFrame, you can use the following syntax to calculate the number of missing values for each of the columns:

missing_values_count = df.isna().sum()

To find the sum of values in a particular column, use the following syntax:

df = pd.read_csv(file.csv)
total = df['name of the column'].sum()

Task

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You are given a DataFrame named audi_cars.

Get the count of non-null cells in each column and store the result in the number_of_cells variable.
Compute the total price (using the 'price' column) for all cars in the DataFrame and store the result in the total_price variable.
Identify the number of missing values in each column and store the result in the null_count variable.

Solution

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Section 3. Chapter 14

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pandas offers the count() method, which counts all non-null cells (neither None nor NaN) for each column.

df = pd.read_csv(file.csv)
number_of_cells = df.count()

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

df = pd.read_csv(file.csv)
number_of_cells = df['name of the column'].count()

pandas also provides the sum() method. This method calculates the sum of values for each column, but it only works with numeric or boolean columns.

df = pd.read_csv(file.csv)
total = df.sum()

Since the isna() method returns a boolean DataFrame, you can use the following syntax to calculate the number of missing values for each of the columns:

missing_values_count = df.isna().sum()

To find the sum of values in a particular column, use the following syntax:

df = pd.read_csv(file.csv)
total = df['name of the column'].sum()

Task

Swipe to start coding

You are given a DataFrame named audi_cars.

Get the count of non-null cells in each column and store the result in the number_of_cells variable.
Compute the total price (using the 'price' column) for all cars in the DataFrame and store the result in the total_price variable.
Identify the number of missing values in each column and store the result in the null_count variable.

Solution

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 3. Chapter 14

single

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pandas offers the count() method, which counts all non-null cells (neither None nor NaN) for each column.

df = pd.read_csv(file.csv)
number_of_cells = df.count()

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

df = pd.read_csv(file.csv)
number_of_cells = df['name of the column'].count()

pandas also provides the sum() method. This method calculates the sum of values for each column, but it only works with numeric or boolean columns.

df = pd.read_csv(file.csv)
total = df.sum()

Since the isna() method returns a boolean DataFrame, you can use the following syntax to calculate the number of missing values for each of the columns:

missing_values_count = df.isna().sum()

To find the sum of values in a particular column, use the following syntax:

df = pd.read_csv(file.csv)
total = df['name of the column'].sum()

Task

Swipe to start coding

You are given a DataFrame named audi_cars.

Get the count of non-null cells in each column and store the result in the number_of_cells variable.
Compute the total price (using the 'price' column) for all cars in the DataFrame and store the result in the total_price variable.
Identify the number of missing values in each column and store the result in the null_count variable.

Solution

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

sum() and count()

Solution

Awesome!

sum() and count()

Solution

Awesome!

sum() and count()

Solution