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Statistics for Data Science with Python

Examine the Dataset

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In this section, a sample of IT specialists' salaries will be analyzed. Begin by examining the first five observations of the dataset:

  • work_year - this year, the salary was paid;
  • experience_level - the experience level: EN is Entery-level, MI is Mid-level, SE-Senior-level, EX is Executive level;
  • job_title - the name of a job;
  • salary - the value of the salary;
  • salary_currency - the currency of the salary;
  • salary_in_usd - the value of the salary in USD;
  • company_location - the location of the company;
  • company_size - the size of the company: S-Small, M-Medium, L-Large.

Now begins a review of data types in statistics, followed by an activity to match each column name with its corresponding data type.

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Match the column name with its type.

work_year
experience_level
salary_currency
salary_in_usd
company_size

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Var allt tydligt?

Hur kan vi förbättra det?

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Avsnitt 1. Kapitel 9

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Examine the Dataset

In this section, a sample of IT specialists' salaries will be analyzed. Begin by examining the first five observations of the dataset:

  • work_year - this year, the salary was paid;
  • experience_level - the experience level: EN is Entery-level, MI is Mid-level, SE-Senior-level, EX is Executive level;
  • job_title - the name of a job;
  • salary - the value of the salary;
  • salary_currency - the currency of the salary;
  • salary_in_usd - the value of the salary in USD;
  • company_location - the location of the company;
  • company_size - the size of the company: S-Small, M-Medium, L-Large.

Now begins a review of data types in statistics, followed by an activity to match each column name with its corresponding data type.

Var allt tydligt?

Hur kan vi förbättra det?

Tack för dina kommentarer!

Avsnitt 1. Kapitel 9
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