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IXIena / data-circle-team-a

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choosing the features (columns) #11

Open IXIena opened 1 month ago

IXIena commented 1 month ago

an idea is to filter by the country, after choosing the features decide what to do (eg. impute) if anything with missing values in the chosen columns explore the technical data like languages and databases - which are the most frequent - show the frequency for the first demo

IXIena commented 1 month ago
  1. Age: Age can often correlate with salary as more experienced professionals tend to earn higher salaries.
  2. Employment: This could indicate whether the respondent is employed or not, which is essential for predicting salary.
  3. RemoteWork: Remote work might impact salary depending on location and industry norms.
  4. YearsCode and YearsCodePro: These could signify the years of experience, which often translates to higher salaries.
  5. EdLevel: Higher levels of education might lead to higher-paying jobs.
  6. ConvertedCompYearly: This is likely to be a crucial feature as it directly relates to the total compensation.
  7. Country: Location can significantly affect salary due to cost of living differences.
  8. LanguageHaveWorkedWith, DatabaseHaveWorkedWith, etc.: Skills in certain languages or technologies might command higher salaries.