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Logistic Regression Mastering
Logistic Regression Mastering
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.
Swipe to show code editor
-
Import
pandas
(aspd
) library. -
Import the
"experiment_data.csv"
usingpandas
. -
Display the first 10 rows of the DataFrame.
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