Course Content

Advanced Techniques in pandas

1. Getting Familiar With Indexing and Selecting Data

Outputting Columns by Title Outputting Rows by Index Selecting Specific Rows and Columns Learning More About Indexation Getting Familiar With lambda Functions Expanding Functionality of the .iloc[] Attribute

2. Dealing With Conditions

Setting Condition Selecting Data Based on Condition Dealing With Several Conditions Making Your Code Beautiful Conditions Quiz

3. Extracting Data

Is Data in ...?Combining Your Knowledge Between Method Extracting Specific Data Finding the Smallest Values of a Column Finding the Largest Values of a Column Finding the Correlation

4. Aggregating Data

Getting Familiar With the .groupby() Method Grouping by Several Columns Complicated Grouping Advanced Grouping Dealing With Pivot Tables Creating a Pivot Table

5. Preprocessing Data

Checking for Missing Values Calculating the Number of Missing Values What Will We Do With the NaN Values?How to Delete Only NaN Values?Filling In the Missing Values Managing Categorical Variables Checking the Column Type Managing an Incorrect Column Renaming the Column

Making Your Code Beautiful

Let's make our code more convenient and more readable. By the way, it is essential to make your code understandable for your coworkers.

To simplify the code, we can write the condition first and then put it into the .loc[] function; look at the example from the previous chapter:

The first and second methods lead to the same output, but the second is much better for understanding because you can work with two conditions separately, and the statement within the .loc[] function takes up less space.

Task

Swipe to show code editor

Your task here is to consolidate knowledge from this chapter. You need to extract data on small asteroids with a high magnitude, or hazardous ones. To do so, follow the algorithm:

Write the first condition: values from the column'est_diameter_min' are less than 0.01. Assign it to the variable condition_1.
Write the second condition: values from the column 'absolute_magnitude' are greater than 20. Assign it to the variable condition_2.
Write the third condition: values from the column 'hazardous' are equal to False. Assign it to the variable condition_3.
Write the general condition that satisfies the requirement: (condition_1 and condition_2) or condition_3.

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Section 2. Chapter 4

Making Your Code Beautiful

Let's make our code more convenient and more readable. By the way, it is essential to make your code understandable for your coworkers.

To simplify the code, we can write the condition first and then put it into the .loc[] function; look at the example from the previous chapter:

Task

Swipe to show code editor

Your task here is to consolidate knowledge from this chapter. You need to extract data on small asteroids with a high magnitude, or hazardous ones. To do so, follow the algorithm:

Write the first condition: values from the column'est_diameter_min' are less than 0.01. Assign it to the variable condition_1.
Write the second condition: values from the column 'absolute_magnitude' are greater than 20. Assign it to the variable condition_2.
Write the third condition: values from the column 'hazardous' are equal to False. Assign it to the variable condition_3.
Write the general condition that satisfies the requirement: (condition_1 and condition_2) or condition_3.

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 2. Chapter 4

Making Your Code Beautiful

Let's make our code more convenient and more readable. By the way, it is essential to make your code understandable for your coworkers.

To simplify the code, we can write the condition first and then put it into the .loc[] function; look at the example from the previous chapter:

Task

Swipe to show code editor

Your task here is to consolidate knowledge from this chapter. You need to extract data on small asteroids with a high magnitude, or hazardous ones. To do so, follow the algorithm:

Write the first condition: values from the column'est_diameter_min' are less than 0.01. Assign it to the variable condition_1.
Write the second condition: values from the column 'absolute_magnitude' are greater than 20. Assign it to the variable condition_2.
Write the third condition: values from the column 'hazardous' are equal to False. Assign it to the variable condition_3.
Write the general condition that satisfies the requirement: (condition_1 and condition_2) or condition_3.

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

Everything was clear?

Thanks for your feedback!

Let's make our code more convenient and more readable. By the way, it is essential to make your code understandable for your coworkers.

To simplify the code, we can write the condition first and then put it into the .loc[] function; look at the example from the previous chapter:

Task

Swipe to show code editor

Your task here is to consolidate knowledge from this chapter. You need to extract data on small asteroids with a high magnitude, or hazardous ones. To do so, follow the algorithm:

Write the first condition: values from the column'est_diameter_min' are less than 0.01. Assign it to the variable condition_1.
Write the second condition: values from the column 'absolute_magnitude' are greater than 20. Assign it to the variable condition_2.
Write the third condition: values from the column 'hazardous' are equal to False. Assign it to the variable condition_3.
Write the general condition that satisfies the requirement: (condition_1 and condition_2) or condition_3.

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

Section 2. Chapter 4

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