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main.py
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main.py
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from operator import index
import pandas as pd
from pandas.core.frame import DataFrame as DataFrame
# 책 데이터가 구로, 광주, 하남, 이천, 의정부, 양주가 있으므로, 이 지역의 투표 값을 가져옴
# 거소·선상투표, 관외사전투표, 국외부재자투표 수는 지역 도서량에 따른 투표에 연관되어있지 않기 때문에 드랍
# pd.read_excel('./data/지역구/9경기/개표상황(투표구별)')
def process_dataframe(df: DataFrame) -> DataFrame:
df = df.drop(index=[0, 1, 4, len(df)-1])
df_member_df = df.loc[3]
df_member_df = df_member_df.dropna()
df_member_list = list()
for i in list(df_member_df):
if '\n' in i:
temp_text = i.split('\n')
if temp_text[0]:
df_member_list.append(temp_text[0])
df_column_pre = df.loc[2]
df_column_pre = df_column_pre.drop(df_column_pre.tail(2).index)
df_column_pre = df_column_pre.dropna()
df_column = pd.concat([df_column_pre, pd.DataFrame(df_member_list)])
df_column = df_column[~df_column[0].str.contains("후보자별 득표수")]
df = df.drop(index=[2, 3])
df_left = df[df.columns[: len(df_column)]]
df_left = df_left.reset_index(drop=True)
df_right = df[df.columns[-2: ]]
df_right = df_right.reset_index(drop=True)
df_dataset = pd.merge(df_left, df_right, how='outer', left_index=True, right_index=True)
df_column = pd.concat([df_column, pd.DataFrame(["무효 투표수", "기권수"])])
df_dataset.columns = [*list(df_column.reset_index().drop(columns=['index'])[0])]
# df_dataset['취소표'] = df_dataset['무효 투표수'].add(df_dataset['기권수'])
df_dataset = df_dataset.drop(columns=['무효 투표수', '기권수'])
df_dataset = df_dataset.drop(index=range(5, len(df_dataset)), columns=['투표구명'])
return df_dataset
# 구로
gr_gab = pd.read_excel('C:\\Users\\wayma\\OneDrive\\문서\\GitHub\\2nd-Public-Data-Utilization-Contest-Preprocessing\\20vote\\지역구\\1서울\\개표상황(투표구별)_구로구갑.xlsx')
gr_uel = pd.read_excel('C:\\Users\\wayma\\OneDrive\\문서\\GitHub\\2nd-Public-Data-Utilization-Contest-Preprocessing\\20vote\\지역구\\1서울\\개표상황(투표구별)_구로구을.xlsx')
gr_gab_dataset = process_dataframe(gr_gab)
gr_uel_dataset = process_dataframe(gr_uel)
gr_dataset = gr_gab_dataset.add(gr_uel_dataset, fill_value=0)
for index, item in enumerate(gr_dataset['읍면동명']):
gr_dataset['읍면동명'][index] = item[0:len(item)//2]
gr_dataset.index = gr_dataset['읍면동명']
gr_dataset = gr_dataset.drop(columns=['읍면동명'])
gr_dataset = gr_dataset.drop(columns=['무효 투표수', '기권수'])
# 광주
gj_gab = pd.read_excel('C:\\Users\\wayma\\OneDrive\\문서\\GitHub\\2nd-Public-Data-Utilization-Contest-Preprocessing\\20vote\\지역구\\9경기\\개표상황(투표구별)_광주시갑.xlsx')
gj_uel = pd.read_excel('C:\\Users\\wayma\\OneDrive\\문서\\GitHub\\2nd-Public-Data-Utilization-Contest-Preprocessing\\20vote\\지역구\\9경기\\개표상황(투표구별)_광주시을.xlsx')
gj_gab_dataset = process_dataframe(gj_gab)
gj_uel_dataset = process_dataframe(gj_uel)
gj_dataset = gj_gab_dataset.add(gj_uel_dataset, fill_value=0)
for index, item in enumerate(gj_dataset['읍면동명']):
gj_dataset['읍면동명'][index] = item[0:len(item)//2]
gj_dataset.index = gj_dataset['읍면동명']
gj_dataset = gj_dataset.drop(columns=['읍면동명'])
gj_dataset = gj_dataset.drop(columns=['무효 투표수', '기권수'])
# 하남
hn_dataframe = pd.read_excel('C:\\Users\\wayma\\OneDrive\\문서\\GitHub\\2nd-Public-Data-Utilization-Contest-Preprocessing\\20vote\\지역구\\9경기\\개표상황(투표구별)_하남시.xlsx')
hn_dataset = process_dataframe(hn_dataframe)
hn_dataset.index = hn_dataset['읍면동명']
hn_dataset = hn_dataset.drop(columns=['읍면동명'])
hn_dataset = hn_dataset.drop(columns=['무효 투표수', '기권수'])
# 이천
ic_dataframe = pd.read_excel('C:\\Users\\wayma\\OneDrive\\문서\\GitHub\\2nd-Public-Data-Utilization-Contest-Preprocessing\\20vote\\지역구\\9경기\\개표상황(투표구별)_이천시.xlsx')
ic_dataset = process_dataframe(ic_dataframe)
ic_dataset.index = ic_dataset['읍면동명']
ic_dataset = ic_dataset.drop(columns=['읍면동명'])
ic_dataset = ic_dataset.drop(columns=['무효 투표수', '기권수'])
# 의정부
ijb_gab = pd.read_excel('C:\\Users\\wayma\\OneDrive\\문서\\GitHub\\2nd-Public-Data-Utilization-Contest-Preprocessing\\20vote\\지역구\\9경기\\개표상황(투표구별)_의정부시갑.xlsx')
ijb_uel = pd.read_excel('C:\\Users\\wayma\\OneDrive\\문서\\GitHub\\2nd-Public-Data-Utilization-Contest-Preprocessing\\20vote\\지역구\\9경기\\개표상황(투표구별)_의정부시을.xlsx')
ijb_gab_dataset = process_dataframe(ijb_gab)
ijb_uel_dataset = process_dataframe(ijb_uel)
ijb_dataset = ijb_gab_dataset.add(ijb_uel_dataset, fill_value=0)
for index, item in enumerate(ijb_dataset['읍면동명']):
ijb_dataset['읍면동명'][index] = item[0:len(item)//2]
ijb_dataset.index = ijb_dataset['읍면동명']
ijb_dataset = ijb_dataset.drop(columns=['읍면동명'])
ijb_dataset = ijb_dataset.drop(columns=['무효 투표수', '기권수'])
# 양주
yj_dataframe = pd.read_excel('C:\\Users\\wayma\\OneDrive\\문서\\GitHub\\2nd-Public-Data-Utilization-Contest-Preprocessing\\20vote\\지역구\\9경기\\개표상황(투표구별)_양주시.xlsx')
yj_dataset = process_dataframe(yj_dataframe)
yj_dataset.index = yj_dataset['읍면동명']
yj_dataset = yj_dataset.drop(columns=['읍면동명'])
yj_dataset = yj_dataset.drop(columns=['무효 투표수', '기권수'])
# save to csv
gr_dataset.to_csv('C:\\Users\\wayma\\OneDrive\\문서\\GitHub\\2nd-Public-Data-Utilization-Contest-Preprocessing\\20vote\\preprocessed\\vote_guro.csv', encoding='utf-8-sig')
gj_dataset.to_csv('C:\\Users\\wayma\\OneDrive\\문서\\GitHub\\2nd-Public-Data-Utilization-Contest-Preprocessing\\20vote\\preprocessed\\vote_gwangju.csv')
hn_dataset.to_csv('C:\\Users\\wayma\\OneDrive\\문서\\GitHub\\2nd-Public-Data-Utilization-Contest-Preprocessing\\20vote\\preprocessed\\vote_hanam.csv')
ic_dataset.to_csv('C:\\Users\\wayma\\OneDrive\\문서\\GitHub\\2nd-Public-Data-Utilization-Contest-Preprocessing\\20vote\\preprocessed\\vote_icheon.csv')
ijb_dataset.to_csv('C:\\Users\\wayma\\OneDrive\\문서\\GitHub\\2nd-Public-Data-Utilization-Contest-Preprocessing\\20vote\\preprocessed\\vote_uijeongbu.csv')
yj_dataset.to_csv('C:\\Users\\wayma\\OneDrive\\문서\\GitHub\\2nd-Public-Data-Utilization-Contest-Preprocessing\\20vote\\preprocessed\\vote_yangju.csv')