course content

Course Content

Learning Statistics with Python

Examine DatasetExamine Dataset

In this section, we will work with a sample of the IT specialists' salaries. First look at the first five observations of the dataset:

work_yearexperience_leveljob_titlesalarysalary_currencysalary_in_usdcompany_locationcompany_size
02020MIData Scientist70000EUR79833DEL
12020SEMachine Learning Scientist260000USD260000JPS
22020SEBig Data Engineer85000GBP109024GBM
32020MIProduct Data Analyst20000USD20000HNS
42020SEMachine Learning Engineer150000USD150000USL
  • 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, we will revise the data types in statistics, and after that, you will match the column name and its type.

Types of Data
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Match the column name and its type.

work_year
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experience_level
___

salary_currency
___

salary_in_usd
___

company_size
___

Click or drag`n`drop items and fill in the blanks

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Categorical Ordinal
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Numerical Continious
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Categorical Nominal
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Categorical Ordinal
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Numerical Discrete
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Section 2.

Chapter 1