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Recall Loops | Explore Dataset
Introduction to Python for Data Analysis
course content

Course Content

Introduction to Python for Data Analysis

Introduction to Python for Data Analysis

1. Introduction to Python 1/2
2. Introduction to Python 2/2
3. Explore Dataset
4. Becoming an Analyst

bookRecall Loops

Imagine that you want to count how many 'Data Scientist' jobs are in the dataset. You are already familiar with the loops and if/else statements. Try it.

Task

Follow the algorithm:

  1. Create a for loop that iterates through the 'job_title' column in the df.
  2. Within the for loop, implement the if statement that checks if i is equal to 'Data Scientist'.
  3. Within the if statement, increase the count variable by 1.

In this chapter, you count values in a straightforward but irrational way. Imagine that you have thousands of rows in the dataset; such a loop may take even an hour to process, depending on the dataset's size and the computer's power. Thus, in the next section, you will learn how to do the same thing but in a way that pandas offer you.

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Section 3. Chapter 12
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bookRecall Loops

Imagine that you want to count how many 'Data Scientist' jobs are in the dataset. You are already familiar with the loops and if/else statements. Try it.

Task

Follow the algorithm:

  1. Create a for loop that iterates through the 'job_title' column in the df.
  2. Within the for loop, implement the if statement that checks if i is equal to 'Data Scientist'.
  3. Within the if statement, increase the count variable by 1.

In this chapter, you count values in a straightforward but irrational way. Imagine that you have thousands of rows in the dataset; such a loop may take even an hour to process, depending on the dataset's size and the computer's power. Thus, in the next section, you will learn how to do the same thing but in a way that pandas offer you.

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 12
toggle bottom row

bookRecall Loops

Imagine that you want to count how many 'Data Scientist' jobs are in the dataset. You are already familiar with the loops and if/else statements. Try it.

Task

Follow the algorithm:

  1. Create a for loop that iterates through the 'job_title' column in the df.
  2. Within the for loop, implement the if statement that checks if i is equal to 'Data Scientist'.
  3. Within the if statement, increase the count variable by 1.

In this chapter, you count values in a straightforward but irrational way. Imagine that you have thousands of rows in the dataset; such a loop may take even an hour to process, depending on the dataset's size and the computer's power. Thus, in the next section, you will learn how to do the same thing but in a way that pandas offer you.

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!

Imagine that you want to count how many 'Data Scientist' jobs are in the dataset. You are already familiar with the loops and if/else statements. Try it.

Task

Follow the algorithm:

  1. Create a for loop that iterates through the 'job_title' column in the df.
  2. Within the for loop, implement the if statement that checks if i is equal to 'Data Scientist'.
  3. Within the if statement, increase the count variable by 1.

In this chapter, you count values in a straightforward but irrational way. Imagine that you have thousands of rows in the dataset; such a loop may take even an hour to process, depending on the dataset's size and the computer's power. Thus, in the next section, you will learn how to do the same thing but in a way that pandas offer you.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 3. Chapter 12
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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