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Pandas First Steps
course content

Course Content

Pandas First Steps

Pandas First Steps

1. The Very First Steps
What is pandas? SeriesCreating a SeriesDataFrameSeries QuizCreating a DataFrame QuizAdding a New ColumnInserting a New ColumnDeleting a Row/Column Matching the FunctionsWorking with ColumnsExtracting Columns Quiziloc BasicsUsing iloc
2. Reading Files in Pandas
CSV FilesTXT FilesWorking with Files QuizAccessing the Columns
3. Analyzing the Data
Viewing the DataHead QuizHead and Tail QuizInformation on the DataColumn Names and Data TypesFinding Null ValuesIdentifying Null Values QuizDropping Null ValuesFilling Null ValuesNull Values QuizDescribing the DataCalculating Descriptive Statisticsmax() and min()Statistical Operations Quizsum() and count()Unique Values

booksum() 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
test

Swipe to show code editor

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.

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Section 3. Chapter 15
toggle bottom row

booksum() 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
test

Swipe to show code editor

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.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 3. Chapter 15
toggle bottom row

booksum() 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
test

Swipe to show code editor

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.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

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
test

Swipe to show code editor

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.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 3. Chapter 15
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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