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Change bool to int, separate location

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This commit is contained in:
Aleksey Filippov 2023-06-06 00:33:08 +04:00
parent 5089eb4b10
commit 0eefc9fde0
1 changed files with 14 additions and 9 deletions
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23
src/main/df_loader.py
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@ -2,7 +2,6 @@ from datetime import date
import numpy as np
import pandas as pd
from numpy import ndarray
from pandas import DataFrame
from src.main.constants import Constants as const
@ -49,27 +48,33 @@ class DfLoader:
def __prepare_dataset_status(self) -> None:
is_univer_mask = ((self.__df['age'] >= const.university_gr_age()) | (self.__df['age'] == const.empty_age())) & \
((self.__df['universities'].str.len() > 0) | (self.__df['occupation_type'] == 'university'))
self.__df['is_university'] = np.where(is_univer_mask, True, False)
self.__df['is_university'] = np.where(is_univer_mask, 1, 0)
is_work_mask = ((self.__df['age'] > const.school_gr_age()) | (self.__df['age'] == const.empty_age())) & \
((self.__df['is_university']) | (self.__df['occupation_type'] == 'work')) | \
((self.__df['is_university'] == 1) | (self.__df['occupation_type'] == 'work')) | \
(self.__df['age'] > const.university_gr_age())
self.__df['is_work'] = np.where(is_work_mask, True, False)
self.__df['is_work'] = np.where(is_work_mask, 1, 0)
is_student_mask = ((self.__df['occupation_type'] == 'university') &
((self.__df['age'] >= const.school_gr_age()) &
(self.__df['age'] <= const.university_gr_age())))
self.__df['is_student'] = np.where(is_student_mask, True, False)
self.__df['is_student'] = np.where(is_student_mask, 1, 0)
is_schoolboy_mask = ((self.__df['age'] < const.school_gr_age()) & (self.__df['age'] != const.empty_age())) | \
((self.__df['age'] == const.empty_age()) & (self.__df['occupation_type'] == 'school'))
self.__df['is_schoolboy'] = np.where(is_schoolboy_mask, True, False)
self.__df['is_schoolboy'] = np.where(is_schoolboy_mask, 1, 0)
def __prepare_dataset_location(self) -> None:
self.__geocache.update_geo_cache(self.__df['city'].unique().tolist())
self.__df['location'] = self.__df['city'] \
.apply(lambda val: '' if Utils.is_empty_str(val) else self.__geocache.get_location(val))
self.__df['location-la'] = self.__df.loc[:, 'location'] \
.apply(lambda val: 0 if Utils.is_empty_collection(val) else val[0])
self.__df['location-lo'] = self.__df.loc[:, 'location'] \
.apply(lambda val: 0 if Utils.is_empty_collection(val) else val[1])
def get_clustering_data(self) -> ndarray:
columns: [] = ['location', 'sex', 'age', 'is_university', 'is_work', 'is_student', 'is_schoolboy']
return self.__df[columns].to_numpy()
def get_clustering_data(self) -> DataFrame:
columns: [] = ['location-la', 'location-lo',
'sex', 'age', 'is_university', 'is_work', 'is_student', 'is_schoolboy']
df = self.__df
return df[columns]