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Lære Import Data | Logistic Regression Mastering
Logistic Regression Mastering
course content

Kursusindhold

Logistic Regression Mastering

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Import Data

We will start by importing our data using the famous pandas library. This is an overview of the features in our dataset:

  • enrollee_id: Unique ID for the candidate;

  • city: City code;

  • city_development _index: Development index of the city (scaled);

  • gender: Gender of the candidate;

  • relevent_experience: Relevant experience of candidate;

  • enrolled_university: Type of University course enrolled, if any;

  • education_level: Education level of the candidate;

  • major_discipline: Education major discipline of the candidate;

  • experience: Candidate's total experience in years;

  • company_size: No of employees in current employer's company;

  • company_type: Type of current employer;

  • lastnewjob: Difference in years between previous job and current job;

  • training_hours: training hours completed;

  • target: 0 – Not looking for a job change, 1 – Looking for a job change.

Methods description

Modules and Methods Used

  • pandas: Module for data manipulation and analysis;
    • `.read_csv()**: Function to read a CSV file into a DataFrame;
    • .head(): Method to display the first n rows of a DataFrame.
Opgave

Swipe to start coding

  1. Import pandas (as pd) library.

  2. Import the "experiment_data.csv" using pandas.

  3. Display the first 10 rows of the DataFrame.

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