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nh2020.py
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import os
import re
import numpy as np
import pandas as pd
import electioncleaner as EC
DataFrame = pd.core.frame.DataFrame
Series = pd.core.series.Series
def load_file_federal_1(file: str) -> DataFrame:
data_dict = pd.read_excel(file, sheet_name=None, header=[1, 3])
# Preparse
# We keep the header of the first sheet, which includes full names of candidates
# which we will use for the other sheets
first_sheet_name = [x for x in data_dict.keys() if x.upper().startswith('SUM')][0]
first_sheet_header = data_dict[first_sheet_name].columns
# First sheet includes summary statistics, which we drop
valid_rows = list()
valid = False
for (_, row) in data_dict[first_sheet_name].iterrows():
if not pd.isna(row[0]) and row[0].endswith('County'):
valid = True
if valid:
valid_rows.append(row)
data_dict[first_sheet_name] = pd.DataFrame(valid_rows[1:]).reset_index(drop=True)
data_dict[first_sheet_name].columns = pd.MultiIndex.from_tuples(
[('', valid_rows[0][0])] + [cell for cell in first_sheet_header[1:]])
# Last sheet includes results from two counties, which we split
last_sheet_name = [x for x in data_dict.keys() if x.upper().startswith('STRA')][0]
first_county_rows = list()
second_county_rows = list()
in_second_county = False
for (_, row) in data_dict[last_sheet_name].iterrows():
if pd.isna(row[0]):
continue
if row[0].endswith('County'):
in_second_county = True
if in_second_county:
second_county_rows.append(row)
else:
first_county_rows.append(row)
first_county = data_dict[last_sheet_name].columns[0][1]
second_county = second_county_rows[0][0]
data_dict[first_county] = pd.DataFrame(first_county_rows)
data_dict[second_county] = pd.DataFrame(second_county_rows[1:]).reset_index(drop=True)
data_dict[second_county].columns = pd.MultiIndex.from_tuples(
[('', second_county)] + [cell for cell in data_dict[second_county].columns[1:]])
data_dict.pop(last_sheet_name)
for (sheet_name, county_data) in data_dict.items():
# Drop empty/quasi-empty columns
for column in county_data.columns.copy():
values = set(county_data[column].fillna(''))
if values in [{''}, {'', ' '}]:
county_data = county_data.drop(column, axis=1)
# Drop empty/quasi-empty rows
for (index, row) in county_data.copy().iterrows():
values = set(row.fillna(''))
if values in [{''}, {'', ' '},
{'*correction received', ''},
{'*corrections received', ''}]:
county_data = county_data.drop(index)
county_data = county_data.drop(county_data.tail(1).index) # Drop TOTALS
data_dict[sheet_name] = county_data
first_sheet_header = first_sheet_header[:len(data_dict[first_sheet_name].columns)]
for (sheet_name, county_data) in data_dict.items():
# Use full names for candidates for the sheets
county_data.columns = pd.MultiIndex.from_tuples(
[county_data.columns[0]] + [cell for cell in first_sheet_header[1:]])
data_dict[sheet_name] = county_data
# Now we are ready to merge
file_data = pd.DataFrame()
for (sheet_name, county_data) in data_dict.items():
office = county_data.columns[1][0]
county = county_data.columns[0][1][:-7].strip()
county_data.columns = ['Precinct'] + [cell[1] for cell in county_data.columns[1:]]
county_data = county_data.melt(id_vars=['Precinct'],
var_name='Candidate', value_name='Votes')
county_data['County'] = county
county_data['Office'] = office.strip()
county_data['District'] = ''
county_data['Candidate'] = county_data['Candidate'].str.strip()
county_data['Votes'] = county_data['Votes'].fillna(0).astype(str).replace({'-': 0})
county_data['Votes'] = county_data['Votes'].astype(float).astype(int)
# Do float then int because int('3964.0') yields a value error
county_data = EC.split_column(county_data, 'Candidate',
r'(?P<Candidate>[^,]*) (?P<Party>[^ ]+)',
maintaining_columns=['Candidate'],
empty_value='NONPARTISAN',)
county_data = EC.split_column(county_data, 'Candidate',
r'(?P<Candidate>.*), (?P<Party>[^ ]+)',
maintaining_columns=['Candidate', 'Party'],
empty_value='NONPARTISAN',)
file_data = file_data.append(county_data)
file_data = file_data.reset_index(drop=True).sort_values('County')
return file_data
def load_files_federal_1() -> DataFrame:
files = [
'governor-2020.xls',
'president-2020.xls',
'us-senator-2020.xls',
]
data = pd.DataFrame()
for file in files:
print(f'*Reading file raw/{file}...')
file_data = load_file_federal_1(f'raw/{file}')
data = data.append(file_data)
print(f'Read file raw/{file}...')
data = data.reset_index(drop=True)
data['Precinct'] = data['Precinct'].replace({
r'\*': '',
r'At\. & Gil\. Academy Grant': 'Atkinson and Gilmanton Academy Grant',
r'Atk\. & Gilm\. Ac\. Gt\.': 'Atkinson and Gilmanton Academy Grant',
r"Low & Burbank's Gt\.": "Low and Burbank's Grant",
r"Low & Burbank's Grant": "Low and Burbank's Grant",
r"Second College Gt\.": "Second College Grant",
r"Thompson & Mes's Pur\.": "Thompson and Meserve's Purchase",
r"Thompson & Meserve's Pur\.": "Thompson and Meserve's Purchase",
r"Wentworth's Loc\.": "Wentworth's Location",
}, regex=True).str.strip()
data['Stage'] = 'GEN'
return data
def load_file_federal_2(file: str) -> DataFrame:
data_dict = pd.read_excel(file, sheet_name=None, header=[1, 2], skipfooter=3)
for (sheet_name, county_data) in data_dict.items():
# Drop empty/quasi-empty columns
for column in county_data.columns.copy():
values = set(county_data[column].fillna(''))
if values in [{''}, {'', ' '}]:
county_data = county_data.drop(column, axis=1)
data_dict[sheet_name] = county_data
# Now we are ready to merge
file_data = pd.DataFrame()
for (sheet_name, county_data) in data_dict.items():
raw_office = county_data.columns[1][0]
match = re.match(r'(?P<office>[^-]+)( -)? District (No\. )?(?P<district>\d+)', raw_office)
office, district = match['office'], match['district']
county_data.columns = ['Precinct'] + [cell[1] for cell in county_data.columns[1:]]
county_data = county_data.melt(id_vars=['Precinct'],
var_name='Candidate', value_name='Votes')
county_data['Office'] = office
county_data['District'] = district
county_data['Candidate'] = county_data['Candidate'].str.strip()
county_data['Votes'] = county_data['Votes'].fillna(0).astype(str).str.strip()
county_data['Votes'] = county_data['Votes'].replace({'-': 0}).astype(float).astype(int)
# Do float then int because int('3964.0') yields a value error
county_data = EC.split_column(county_data, 'Candidate',
r'(?P<Candidate>[^,]*) (?P<Party>[^ ]+)',
maintaining_columns=['Candidate'],
empty_value='NONPARTISAN',)
county_data = EC.split_column(county_data, 'Candidate',
r'(?P<Candidate>.*), (?P<Party>[^ ]+)',
maintaining_columns=['Candidate', 'Party'],
empty_value='NONPARTISAN',)
file_data = file_data.append(county_data)
file_data = file_data.reset_index(drop=True)
return file_data
def load_files_federal_2() -> DataFrame:
files = [
'congressional-district-1-2020.xlsx',
'congressional-district-2-2020.xlsx',
'executive-council-district-1-5-2020.xls',
]
data = pd.DataFrame()
for file in files:
print(f'*Reading file raw/{file}...')
file_data = load_file_federal_2(f'raw/{file}')
data = data.append(file_data)
print(f'Read file raw/{file}...')
data['Precinct'] = data['Precinct'].replace({
r'\*': '',
r'At\. & Gil Ac\. Gt': 'Atkinson and Gilmanton Academy Grant',
r'Atkinson & Gilmanton Academy Gt': 'Atkinson and Gilmanton Academy Grant',
r"Low & Burbank's Grant": "Low and Burbank's Grant",
r'- Ward': 'Ward',
r"Martins' Location": "Martin's Location",
r"Thomp. and Mes's Pur.": "Thompson and Meserve's Purchase",
r"Thompson & Meserve's Purchase": "Thompson and Meserve's Purchase",
}, regex=True).str.strip()
data = data.reset_index(drop=True)
data['Stage'] = 'GEN'
return data
def load_file_state_senate(file: str) -> DataFrame:
data_dict = pd.read_excel(file, sheet_name=None, header=None)
# Preparse, as a few sheets include multiple races in the same sheet
dfs = dict()
for (sheet, sheet_data) in data_dict.items():
rows = list()
race = ''
for (_, row) in sheet_data.iterrows():
new_row = list()
for value in row:
if pd.isna(value):
new_row.append('')
else:
new_row.append(str(value).strip())
if new_row[1] == 'State of New Hampshire':
continue
if new_row[2] == '':
# Header column
race = new_row[1]
rows = list()
continue
if set(new_row) in [{''}, {'', ' '}]:
# Ignore empty rows
continue
if new_row[0].upper() == 'TOTALS':
# Save dataframe
df = pd.DataFrame(rows[1:])
df.columns = rows[0]
df = df.dropna(axis=1, how='all')
dfs[race] = df
continue
rows.append(row)
# Now we are ready to merge
file_data = pd.DataFrame()
for (sheet_name, race_data) in dfs.items():
match = re.match(r'(?P<office>[^-]+)( -)? District (No\. )?(?P<district>\d+)', sheet_name)
office, district = match['office'], match['district']
race_data.columns = ['Precinct'] + [cell for cell in race_data.columns[1:]]
race_data = race_data.melt(id_vars=['Precinct'],
var_name='Candidate', value_name='Votes')
race_data['Office'] = office
race_data['District'] = district
race_data['Candidate'] = race_data['Candidate'].str.strip()
race_data['Precinct'] = race_data['Precinct'].str.strip()
race_data['Votes'] = race_data['Votes'].fillna(0).astype(str).str.strip()
race_data['Votes'] = race_data['Votes'].replace({'--': 0}).astype(float).astype(int)
# Do float then int because int('3964.0') yields a value error
race_data = EC.split_column(race_data, 'Candidate',
r'(?P<Candidate>.*), (?P<Party>[^ ]+)',
maintaining_columns=['Candidate'],
empty_value='NONPARTISAN',)
file_data = file_data.append(race_data)
file_data = file_data.reset_index(drop=True)
return file_data
def load_files_state_senate() -> DataFrame:
files = [
'state-senate-district-1-11-2020.xls',
'state-senate-district-12-24-2020.xls',
]
data = pd.DataFrame()
for file in files:
print(f'*Reading file raw/{file}...')
file_data = load_file_state_senate(f'raw/{file}')
data = data.append(file_data)
print(f'Read file raw/{file}...')
data = data.reset_index(drop=True)
data['Stage'] = 'GEN'
# A few races had recounts, which were not appropriate labeled. Manually convert them based on
# Precinct and Vote totals
recount_candidates = {
# STATE SENATE DISTRICT 11
('Amherst', 3532): ('Gary L. Daniels', 'r'),
('Merrimack', 8193): ('Gary L. Daniels', 'r'),
('Milford', 4581): ('Gary L. Daniels', 'r'),
('Wilton', 1187): ('Gary L. Daniels', 'r'),
('Amherst', 4409): ('Shannon E. Chandley', 'd'),
('Merrimack', 7588): ('Shannon E. Chandley', 'd'),
('Milford', 4155): ('Shannon E. Chandley', 'd'),
('Wilton', 1182): ('Shannon E. Chandley', 'd'),
# STATE SENATE DISTRICT 12
('Brookline', 1765): ('Kevin Avard', 'r'),
('Greenville', 556): ('Kevin Avard', 'r'),
('Hollis', 2772): ('Kevin Avard', 'r'),
('Mason', 556): ('Kevin Avard', 'r'),
('Nashua Ward 1', 2673): ('Kevin Avard', 'r'),
('Nashua Ward 2', 2127): ('Kevin Avard', 'r'),
('Nashua Ward 5', 2770): ('Kevin Avard', 'r'),
('New Ipswich', 2130): ('Kevin Avard', 'r'),
('Rindge', 2185): ('Kevin Avard', 'r'),
('Brookline', 1799): ('Melanie Levesque', 'd'),
('Greenville', 464): ('Melanie Levesque', 'd'),
('Hollis', 2897): ('Melanie Levesque', 'd'),
('Mason', 367): ('Melanie Levesque', 'd'),
('Nashua Ward 1', 3103): ('Melanie Levesque', 'd'),
('Nashua Ward 2', 2727): ('Melanie Levesque', 'd'),
('Nashua Ward 5', 3118): ('Melanie Levesque', 'd'),
('New Ipswich', 923): ('Melanie Levesque', 'd'),
('Rindge', 1331): ('Melanie Levesque', 'd'),
}
for (key, value) in recount_candidates.items():
precinct, votes = key
candidate, party = value
row = data.index[((data['Precinct'] == precinct) & (data['Candidate'] == 'Recount')
& (data['Votes'] == votes))][0]
data.iat[row, 1] = candidate
data.iat[row, 5] = party
data.iat[row, 6] = 'GEN RECOUNT'
data['Precinct'] = data['Precinct'].replace({
r'\*': '',
r'Atkinson and Gilmanton Ac. Gt.': 'Atkinson and Gilmanton Academy Grant',
r"Low & Burbank's Grant": "Low and Burbank's Grant",
r"Thompson & Meserve's Pur.": "Thompson and Meserve's Purchase"
}, regex=True).str.strip()
return data
def load_file_state_house(file: str) -> DataFrame:
county = re.search(r'house-(?P<county>.*)-2020.xls', file)['county']
raw_data = pd.read_excel(file, sheet_name=0, header=None)
dfs = dict()
rows = list()
race = ''
# Carroll dropped a comma
if county == 'carroll':
raw_data.iat[9, 1] = 'Richardson, r'
# And Coos did not name a district for whatever reason
elif county == 'coos':
raw_data.iat[31, 0] = 'District No. 3'
# And Hillsborough misplaced a few rows:
elif county == 'hillsborough':
raw_data.iat[79, 6] = 'Scatter'
raw_data.iat[80, 6] = 16
# And these are extraneous rows
raw_data.iat[223, 8] = np.nan
raw_data.iat[224, 8] = np.nan
# And dropped a comma
raw_data.iat[175, 2] = 'Hennessey, d'
# And Merrimack did not name a district
elif county == 'merrimack':
raw_data.iat[114, 0] = 'District No. 24'
# And had a space cell
raw_data.iat[112, 7] = np.nan
# And Rockingham misplaced a few rows, so we manually fix them before anything
elif county == 'rockingham':
raw_data.iat[45, 0] = ''
raw_data.iat[46, 0] = 'District No. 6'
raw_data.iat[47, 0] = 'Derry'
# And fix empty cell
raw_data.iat[130, 0] = 'District No. 21'
# And Sullivan has a space cell
elif county == 'sullivan':
raw_data.iat[12, 4] = np.nan
# And Strafford misnamed a district and had an extra value
elif county == 'strafford':
raw_data.iat[58, 0] = 'District No. 15 (1)'
raw_data.iat[122, 4] = ''
def _save_dataframe(rows, race):
df = pd.DataFrame(rows[1:])
df.columns = [str(x).strip() for x in rows[0]]
if '' in df.columns:
df = df.drop(labels='', axis=1)
df = df.dropna(axis=1, how='all')
fixed_races = [race[:-2] for race in dfs.keys()]
race += f'#{fixed_races.count(race)}'
dfs[race] = df
rows.clear()
# Preparse
for (i, row) in raw_data.iterrows():
new_row = list()
for value in row:
if pd.isna(value):
new_row.append('')
else:
new_row.append(str(value).strip())
if i < 2:
# Skip title rows
continue
if set(new_row) == {''}:
# Ignore empty rows...
# Unless we have buffered rows already (which happen if races dont include a totals row)
if not rows:
continue
_save_dataframe(rows, race)
continue
if new_row[0].startswith('District') or new_row[0].startswith('Distict'):
if rows:
_save_dataframe(rows, race)
# Header column
# Magnitude
match = re.search(r'\((?P<magnitude>\d+)\)', new_row[0])
if match:
magnitude = match['magnitude']
if magnitude != '1':
race = f'STATE HOUSE (VOTE FOR {magnitude})'
else:
race = 'STATE HOUSE'
else:
race = 'STATE HOUSE'
# District
match = re.search(r'Distr?ict No\.?( *)(?P<district>\d+).*', new_row[0])
district = match['district']
if 'F' in new_row[0]:
district += 'F'
race += f' - District {district}'
row[0] = race
rows = list()
rows.append(row)
continue
if new_row[0].upper() == 'TOTALS':
_save_dataframe(rows, race)
continue
rows.append(row)
# A few districts straddle rows, so we merge them based on the longest name
new_dfs = dict()
for name in sorted(dfs.keys()):
for other_name in new_dfs.keys():
if other_name[-12:-2] == name[-12:-2]:
new_dfs[other_name] = pd.concat([
new_dfs[other_name].reset_index(drop=True),
dfs[name].drop(dfs[name].columns[0], axis=1).reset_index(drop=True),
], axis=1)
break
else:
new_dfs[name] = dfs[name]
# Now we are ready to merge
file_data = pd.DataFrame()
for (sheet_name, race_data) in new_dfs.items():
match = re.match(r'(?P<office>.+) - District (?P<district>\d+F?)', sheet_name[:-2])
office, district = match['office'], match['district']
race_data.columns = ['Precinct'] + [cell for cell in race_data.columns[1:]]
race_data = race_data.melt(id_vars=['Precinct'],
var_name='Candidate', value_name='Votes')
race_data['County'] = county.capitalize()
race_data['Office'] = office
race_data['District'] = district
race_data['Candidate'] = race_data['Candidate'].str.strip()
race_data['Precinct'] = race_data['Precinct'].str.strip()
race_data['Votes'] = race_data['Votes'].fillna(0).astype(str).str.strip()
race_data['Votes'] = race_data['Votes'].replace({
'.*-.*': 0,
'^$': 0,
}, regex=True).astype(float).astype(int)
# Do float then int because int('3964.0') yields a value error
race_data = EC.split_column(race_data, 'Candidate',
r'(?P<Candidate>.*), ?(?P<Party>[^ ]+)',
maintaining_columns=['Candidate'],
empty_value='NONPARTISAN',)
file_data = file_data.append(race_data)
file_data = file_data.reset_index(drop=True).sort_values('District')
return file_data
def load_files_state_house() -> DataFrame:
files = [
'house-belknap-2020.xls',
'house-carroll-2020.xls',
'house-cheshire-2020.xls',
'house-coos-2020.xls',
'house-grafton-2020.xls',
'house-hillsborough-2020.xls',
'house-merrimack-2020.xls',
'house-rockingham-2020.xls',
'house-strafford-2020.xls',
'house-sullivan-2020.xls',
]
data = pd.DataFrame()
for file in files:
print(f'*Reading file raw/{file}...')
file_data = load_file_state_house(f'raw/{file}')
data = data.append(file_data)
print(f'Read file raw/{file}...')
data = data.reset_index(drop=True)
data['Stage'] = 'GEN'
# A few races had recounts, which were not appropriate labeled. Manually convert them based on
# Precinct and Vote totals
# These ones were listed as columns
recount_candidates = {
# GRAFTON
('17F', 'Hughes', 'r'): {
'Alexandria': 572,
'Ashland': 649,
'Bridgewater': 477,
'Bristol': 1005,
'Enfield': 939,
'Grafton': 406,
},
('17F', 'Adjutant', 'd'): {
'Alexandria': 450,
'Ashland': 524,
'Bridgewater': 358,
'Bristol': 767,
'Enfield': 1695,
'Grafton': 334,
},
# Hillsborough
('4', 'Kofalt', 'r'): {
'Francestown': 521,
'Greenville': 520,
'Lyndeborough': 537,
'Wilton': 1098,
},
('4', 'Post', 'r'): {
'Francestown': 531,
'Greenville': 493,
'Lyndeborough': 576,
'Wilton': 1048,
},
('4', 'Bernet', 'd'): {
'Francestown': 531,
'Greenville': 432,
'Lyndeborough': 476,
'Wilton': 1187,
},
('4', 'Williams', 'd'): {
'Francestown': 496,
'Greenville': 409,
'Lyndeborough': 427,
'Wilton': 1151,
},
# MERRIMACK
('17', 'D. Soucy', 'r'): {
'Concord Ward 8': 1016,
},
('17', 'Wazir', 'd'): {
'Concord Ward 8': 1209,
},
('20', 'Seaworth', 'r'): {
'Chichester': 939,
'Pembroke': 2107,
},
('20', 'White', 'r'): {
'Chichester': 851,
'Pembroke': 1805,
},
('20', 'Gagyi', 'r'): {
'Chichester': 786,
'Pembroke': 1689,
},
('20', 'Hanson, Jr.', 'd'): {
'Chichester': 615,
'Pembroke': 1824,
},
('20', 'Schuett', 'd'): {
'Chichester': 704,
'Pembroke': 2031,
},
('20', 'Doherty', 'd'): {
'Chichester': 669,
'Pembroke': 1967,
},
}
for (key, value) in recount_candidates.items():
district, candidate, party, = key
for (precinct, votes) in value.items():
row = data.index[((data['Precinct'] == precinct) & (data['Candidate'] == 'Recount') &
(data['District'] == district) & (data['Votes'] == votes))][0]
data.iat[row, 1] = candidate
data.iat[row, 6] = party
data.iat[row, 7] = 'GEN RECOUNT'
# These ones were rows
recount_candidates_2 = {
# DISTRICT 15
('Hillsborough', 'McNair', 'r'): {
'Manchester Ward 8': 2437,
},
('Hillsborough', 'Warden', 'r'): {
'Manchester Ward 8': 2612,
},
('Hillsborough', 'Connors', 'd'): {
'Manchester Ward 8': 2454,
},
('Hillsborough', 'Katsiantonis', 'd'): {
'Manchester Ward 8': 1721,
},
# DISTRICT 16
('Hillsborough', 'Kliskey', 'r'): {
'Manchester Ward 9': 1785,
},
('Hillsborough', 'Stefanik', 'r'): {
'Manchester Ward 9': 1720,
},
('Hillsborough', 'Query', 'd'): {
'Manchester Ward 9': 1820,
},
('Hillsborough', 'Shaw', 'd'): {
'Manchester Ward 9': 2336
},
# DISTRICT 19
('Hillsborough', 'Marston', 'r'): {
'Manchester Ward 12': 2019,
},
('Hillsborough', 'Whitlock', 'r'): {
'Manchester Ward 12': 1881,
},
('Hillsborough', 'Snow', 'd'): {
'Manchester Ward 12': 2419,
},
('Hillsborough', 'Zackeroff', 'd'): {
'Manchester Ward 12': 2009,
},
# DISTRICT 34
('Hillsborough', 'Hall', 'r'): {
'Nashua Ward 7': 1787,
},
('Hillsborough', 'Hogan', 'r'): {
'Nashua Ward 7': 1537,
},
('Hillsborough', 'Casey', 'r'): {
'Nashua Ward 7': 1526,
},
('Hillsborough', 'Sofikitis', 'd'): {
'Nashua Ward 7': 2029,
},
('Hillsborough', 'Stevens', 'd'): {
'Nashua Ward 7': 2041,
},
('Hillsborough', 'Moran, Jr.', 'd'): {
'Nashua Ward 7': 1805,
},
# DISTRICT 7
('Rockingham', 'Soti', 'r'): {
'Windham': 4777,
},
('Rockingham', 'Griffin', 'r'): {
'Windham': 5591,
},
('Rockingham', 'Lynn', 'r'): {
'Windham': 5089,
},
('Rockingham', 'McMahon', 'r'): {
'Windham': 5554,
},
('Rockingham', 'St.Laurent', 'd'): {
'Windham': 4357,
},
('Rockingham', 'Azibert', 'd'): {
'Windham': 2808,
},
('Rockingham', 'Roman', 'd'): {
'Windham': 3443,
},
('Rockingham', 'Singureanu', 'd'): {
'Windham': 2782,
},
# DISTRICT 7
('Strafford', 'deBree', 'r'): {
'Rochester Ward 1': 1405,
},
('Strafford', 'Fontneau', 'd'): {
'Rochester Ward 1': 1409,
}
}
for (key, value) in recount_candidates_2.items():
county, candidate, party, = key
for (precinct, votes) in value.items():
row = data.index[((data['Precinct'] == 'Recount') & (data['Candidate'] == candidate) &
(data['Party'] == party) &
(data['County'] == county) & (data['Votes'] == votes))][0]
data.iat[row, 0] = precinct
data.iat[row, 7] = 'GEN RECOUNT'
# There were a few precinct rows that correspond to recounts that also lists scatters. Those
# were not recounted, so they are not included in the final data
data = data[~((data['Precinct'] == 'Recount') &
(data['Votes'] == 0))]
# State House candidates did not include name
# .......sigh
replacements = {
# Belknap
("Belknap", "1", "Joseph, Jr.", "d"): 'Robert Joseph Jr.',
("Belknap", "1", "Ploszaj", "r"): 'Tom Ploszaj',
("Belknap", "2", "Taylor", "d"): 'Natalie Taylor',
("Belknap", "2", "Mackie", "r"): 'Jonathan Mackie',
("Belknap", "2", "Silber", "r"): 'Norman Silber',
("Belknap", "2", "Carita", "d"): 'Shelley Carita',
("Belknap", "2", "Aldrich", "r"): 'Glen Aldrich',
("Belknap", "2", "McCue", "d"): 'Dara McCue',
("Belknap", "2", "Hanley", "d"): 'Diane Hanley',
("Belknap", "2", "Bean", "r"): 'Harry Bean',
("Belknap", "3", "Hough", "r"): 'Gregg Hough',
("Belknap", "3", "Cardona", "d"): 'Carlos Cardona',
("Belknap", "3", "Johnson", "r"): 'Dawn Johnson',
("Belknap", "3", "Ober", "d"): 'Gail Ober',
("Belknap", "3", "Bordes", "r"): 'Mike Bordes',
("Belknap", "3", "Huot", "d"): 'David Huot',
("Belknap", "3", "Hayward", "d"): 'Marcia Hayward',
("Belknap", "3", "Littlefield", "r"): 'Richard Littlefield',
("Belknap", "4", "Harvey-Bolia", "r"): 'Juliet Harvey-Bolia',
("Belknap", "4", "R. Burke (w-in)", "NONPARTISAN"): 'Rich Burke (w-in)',
("Belknap", "4", "Lang, Sr.", "r"): 'Timothy Lang Sr.',
("Belknap", "4", "Alden", "d"): 'Jane Alden',
("Belknap", "5", "Hammond", "d"): 'Duane Hammond',
("Belknap", "5", "Copithorne", "d"): 'Stephen Copithorne',
("Belknap", "5", "Varney", "r"): 'Peter Varney',
("Belknap", "5", "Terry", "r"): 'Paul Terry',
("Belknap", "6", "Sylvia", "r"): 'Michael Sylvia',
("Belknap", "6", "Trottier", "r"): 'Douglas Trottier',
("Belknap", "6", "Condode-metraky", "d"): 'George Condodemetraky',
("Belknap", "6", "House", "d"): 'Don House',
("Belknap", "7", "Comtois", "r"): 'Barbara Comtois',
("Belknap", "7", "Westlake", "d"): 'Jane Westlake',
("Belknap", "8F", "Larson", "d"): 'Ruth Larson',
("Belknap", "8F", "Howard, Jr.", "r"): 'Raymond Howard Jr',
("Belknap", "9F", "St. Clair", "d"): 'Charlie St. Clair',
("Belknap", "9F", "O'Hara", "r"): "Travis O'Hara",
# Carroll
("Carroll", "1", "Gilmore", "r"): 'Ray Gilmore',
("Carroll", "1", "Burroughs", "d"): 'Anita Burroughs',
("Carroll", "2", "McCarthy", "r"): 'Frank McCarthy',
("Carroll", "2", "Umberger", "r"): 'Karen Umberger',
("Carroll", "2", "Richardson", "r"): 'Wendy Richardson',
("Carroll", "2", "Woodcock", "d"): 'Stephen Woodcock',
("Carroll", "2", "Buco", "d"): 'Tom Buco',
("Carroll", "2", "Leonard", "d"): 'Ellin Leonard',
("Carroll", "3", "McConkey", "r"): 'Mark McConkey',
("Carroll", "3", "Ticehurst", "d"): 'Susan Ticehurst',
("Carroll", "3", "Nordlund", "r"): 'Nicole Nordlund',
("Carroll", "3", "Knirk", "d"): 'Jerry Knirk',
("Carroll", "4", "Cordelli", "r"): 'Glenn Cordelli',
("Carroll", "4", "Nesbitt", "d"): 'Caroline Nesbitt',
("Carroll", "4", "Merrill", "d"): 'Chip Merrill',
("Carroll", "4", "Crawford", "r"): 'Karel Crawford',
("Carroll", "5", "Ackerman", "d"): 'Donna Ackerman',
("Carroll", "5", "Pustell", "d"): 'Patricia Pustell',
("Carroll", "5", "Nelson", "r"): 'Bill Nelson',
("Carroll", "5", "Smith", "r"): 'Jonathan Smith',
("Carroll", "5", "Avellani", "r"): 'Lino Avellani',
("Carroll", "5", "Ogren", "d"): 'Knute Ogren',
("Carroll", "6", "Deshaies", "r"): 'Brodie Deshaies',
("Carroll", "6", "MacDonald", "r"): 'John MacDonald',
("Carroll", "6", "Duran", "d"): 'Carrie Duran',
("Carroll", "6", "Wall", "d"): 'John Wall',
("Carroll", "7F", "Tregenza", "r"): 'Norman Tregenza',
("Carroll", "7F", "McAleer", "d"): 'Chris McAleer',
("Carroll", "8F", "Klotz", "d"): 'Eve Klotz',
("Carroll", "8F", "Marsh", "r"): 'William Marsh',
# Cheshire
("Cheshire", "1", "Day", "r"): 'Kate Day',
("Cheshire", "1", "Benik", "r"): 'Peter Benik',
("Cheshire", "1", "Aldrich", "r"): 'Whitney Aldrich',
("Cheshire", "1", "Weber", "d"): 'Lucy McVitty Weber',
("Cheshire", "1", "Harvey", "d"): 'Cathryn A Harvey',
("Cheshire", "1", "Berch", "d"): 'Paul Berch',
("Cheshire", "1", "Abbott", "d"): 'Michael Abbott',
("Cheshire", "1", "Merkt", "r"): 'Richard Merkt',
("Cheshire", "10", "Thackston", "r"): 'Dick Thackston',
("Cheshire", "10", "Parshall", "d"): 'Lucius Parshall',
("Cheshire", "11", "Hunt", "r"): 'John Hunt',
("Cheshire", "11", "Qualey", "r"): 'Jim Qualey',
("Cheshire", "11", "Andersen", "d"): 'Gene Andersen',
("Cheshire", "11", "Martin", "d"): 'Patricia Martin',
("Cheshire", "12", "Gomarlo", "d"): 'Jennie Gomarlo',
("Cheshire", "12", "Faulkner", "d"): 'Barrett Faulkner',
("Cheshire", "12", "Malone", "r"): 'Stephen K Malone',
("Cheshire", "12", "Karasinski", "r"): 'Sly Karasinski',
("Cheshire", "13", "Quevedo", "d"): 'Natalie Quevedo',
("Cheshire", "13", "Kilanski", "r"): 'Ben Kilanski',
("Cheshire", "14F", "Santonastaso", "r"): 'Matthew Santonastaso',
("Cheshire", "14F", "Maneval", "d"): 'Andrew Maneval',
("Cheshire", "15F", "Tatro", "d"): 'Bruce Tatro',
("Cheshire", "15F", "Rhodes", "r"): 'Jennifer Rhodes',
("Cheshire", "16F", "Roach", "r"): 'Matt Roach',
("Cheshire", "16F", "Toll", "d"): 'Amanda Toll',
("Cheshire", "16F", "Schapiro", "d"): 'Joe Schapiro',
("Cheshire", "16F", "Sickels", "r"): 'Jerry Sickels',
("Cheshire", "2", "Nalevanko", "r"): 'Richard Nalevanko',
("Cheshire", "2", "Mann", "d"): 'John Mann',
("Cheshire", "3", "D'Arcy", "r"): "Robert D'Arcy",
("Cheshire", "3", "Eaton", "d"): 'Daniel Eaton',
("Cheshire", "4", "Welkowitz", "d"): 'Lawrence Welkowitz',
("Cheshire", "5", "Huston", "r"): 'Marilyn Huston',
("Cheshire", "5", "Bordenet", "d"): 'John Bordenet',
("Cheshire", "6", "Fox", "d"): 'Dru Fox',
("Cheshire", "6", "LaBrie", "r"): 'Kyle LaBrie',
("Cheshire", "7", "Call", "r"): 'Robert Call',
("Cheshire", "7", "Von Plinsky", "d"): 'Sparky Von Plinsky',
("Cheshire", "8", "Fenton", "d"): 'Donovan Fenton',
("Cheshire", "9", "Ley", "d"): 'Douglas Ley',
("Cheshire", "9", "Ames", "d"): 'Richard Ames',
("Cheshire", "9", "Plante", "r"): 'Leo Plante',
("Cheshire", "9", "Mattson", "r"): 'Rita Mattson',
# Coos
("Coos", "1", "Dostie", "r"): 'Donald Dostie',
("Coos", "1", "Christianson", "d"): 'Bernice Christianson',
("Coos", "1", "Thompson", "r"): 'Dennis Thompson',
("Coos", "1", "Baker", "d"): 'Bob Baker',
("Coos", "2", "Roberge", "d"): 'Christopher Roberge',
("Coos", "2", "Davis", "r"): 'Arnold Davis',
("Coos", "3", "Kelley", "d"): 'Earnon Kelley',
("Coos", "3", "Noel", "d"): 'Henry Noel',
("Coos", "3", "Laflamme", "d"): 'Larry Laflamme',
("Coos", "3", "Evans", "r"): 'Mark Evans',
("Coos", "3", "Theberge", "r"): 'Robert Theberge',
("Coos", "3", "Light", "r"): 'Stuart Light',
("Coos", "4", "Merrick", "d"): 'Evalyn Merrick',
("Coos", "4", "Craig", "r"): 'Kevin Craig',
("Coos", "5", "Tucker", "d"): 'Edith Tucker',
("Coos", "5", "Greer", "r"): 'John Greer',
("Coos", "6", "Hatch", "d"): 'William Hatch',
("Coos", "7F", "Merner", "r"): 'Troy Merner',
("Coos", "7F", "Stocks", "d"): 'Gregor Stocks',
# Grafton
("Grafton", "1", "Beaulier", "r"): 'Calvin Beaulier',
("Grafton", "1", "Sherrard", "d"): 'Sally Sherrard',
("Grafton", "1", "DePalma IV", "r"): 'Joseph DePalma IV',
("Grafton", "1", "Massimilla", "d"): 'Linda Massimilla',
("Grafton", "10", "Dontonville", "d"): 'Roger Dontonville',
("Grafton", "11", "Josephson", "d"): 'Timothy Josephson',
("Grafton", "11", "Folsom", "r"): 'Beth Folsom',
("Grafton", "12", "Hakken-Phillips", "d"): 'Mary Hakken-Phillips',
("Grafton", "12", "Muirhead", "d"): 'Russell Muirhead',
("Grafton", "12", "Murpy", "d"): 'James M Murphy', # Misspelled
("Grafton", "12", "Nordgren", "d"): 'Sharon Nordgren',
("Grafton", "13", "Balog", "r"): 'Michael Balog',
("Grafton", "13", "Flanders", "r"): 'Joshua Flanders',
("Grafton", "13", "Sykes", "d"): 'George Sykes',
("Grafton", "13", "Abel", "d"): 'Richard Abel',
("Grafton", "13", "Almy", "d"): 'Susan Almy',
("Grafton", "13", "Stavis", "d"): 'Laurel Stavis',
("Grafton", "14F", "Simon", "r"): 'Matthew Simon',
("Grafton", "14F", "French", "d"): 'Elaine French',
("Grafton", "15F", "Rajsteter", "d"): 'Ed Rajsteter',
("Grafton", "15F", "Binford", "r"): 'David W Binford',
("Grafton", "16F", "Diggs", "d"): 'Francesca Diggs',
("Grafton", "16F", "Greeson", "r"): 'Jeffrey Greeson',
("Grafton", "17F", "Adjutant", "d"): 'Joshua Adjutant',
("Grafton", "17F", "Hughes", "r"): 'Kendall Hughes',
("Grafton", "2", "Peraino", "r"): 'Robert Peraino',
("Grafton", "2", "Egan", "d"): 'Timothy Egan',
("Grafton", "3", "Chapmon", "r"): 'Wes Chapmon',
("Grafton", "3", "Ruprecht", "d"): 'Denny Ruprecht',
("Grafton", "4", "Ladd", "r"): 'Roderick Ladd',
("Grafton", "4", "LoCascio", "d"): 'Don Locascio',
("Grafton", "5", "Stringham", "d"): 'Jerry Stringham',
("Grafton", "5", "Ham", "r"): 'Bonnie Ham',
("Grafton", "6", "Maes", "d"): 'Kevin Maes',
("Grafton", "6", "Sanborn", "r"): 'Gail Sanborn',
("Grafton", "7", "Alliegro", "r"): 'Mark Alliegro',
("Grafton", "7", "Osborne", "d"): 'Richard Osborne',
("Grafton", "8", "Kirk", "r"): 'George Kirk',
("Grafton", "8", "McLaughlin", "r"): 'Mike McLaughlin',
("Grafton", "8", "Benedetto", "r"): 'Steven Benedetto',
("Grafton", "8", "Smith", "d"): 'Suzanne Smith',
("Grafton", "8", "Weston", "d"): 'Joyce Weston',
("Grafton", "8", "Fellows", "d"): 'Sallie Fellows',
("Grafton", "9", "Berezhny", "r"): 'Lex Berezhny',
("Grafton", "9", "Gordon", "r"): 'Ned Gordon',
("Grafton", "9", "Fluehr-Lobban", "d"): 'Carolyn Fluehr-Lobban',
("Grafton", "9", "Mulholland", "d"): 'Catherine Mulholland',
# Hillsborough
("Hillsborough", "1", "Porter", "d"): 'Marjorie Porter',
("Hillsborough", "1", "Valera", "r"): 'John Valera',
("Hillsborough", "1", "Fedolfi", "r"): 'Jim Fedolfi',
("Hillsborough", "1", "White", "d"): 'Susanne White',
("Hillsborough", "10", "Long", "d"): 'Patrick Long',
("Hillsborough", "10", "Jeudy", "d"): 'Jean Jeudy',
("Hillsborough", "10", "Beene", "r"): 'Holly Beene',
("Hillsborough", "11", "Hodgdon", "r"): 'Jason Hodgdon',
("Hillsborough", "11", "Hagala", "r"): 'Richard Hagala',
("Hillsborough", "11", "Knight", "d"): 'Nicole Klein-Knight',
("Hillsborough", "11", "Bouchard", "d"): 'Donald Bouchard',
("Hillsborough", "11", "Daniel", "l"): 'Robert Daniel',
("Hillsborough", "12", "Poisson", "r"): 'Sharon Poisson',
("Hillsborough", "12", "Amanda Bouldin", "d"): 'Amanda Bouldin',
("Hillsborough", "12", "Andrew Bouldin", "d"): 'Andrew Bouldin',
("Hillsborough", "12", "Spencer", "r"): 'Constance Spencer',
("Hillsborough", "13", "Gagne", "r"): 'Larry Gagne',
("Hillsborough", "13", "Infantine", "r"): 'William Infantine',
("Hillsborough", "13", "Hamilton", "d"): 'Christy Hamilton',
("Hillsborough", "13", "Dion", "d"): 'Darryl Dion',
("Hillsborough", "14", "Heath", "d"): 'Mary Heath',
("Hillsborough", "14", "Freitas", "d"): 'Mary Freitas',
("Hillsborough", "14", "Focht", "r"): 'Steve Focht',
("Hillsborough", "14", "Cole", "r"): 'Brian Cole',
("Hillsborough", "15", "Katsiantonis", "d"): 'Thomas Katsiantonis',
("Hillsborough", "15", "Warden", "r"): 'Mark Warden',
("Hillsborough", "15", "McNair", "r"): 'Macy McNair',
("Hillsborough", "15", "Connors", "d"): 'Erika Connors',
("Hillsborough", "16", "Shaw", "d"): 'Barbara Shaw',
("Hillsborough", "16", "Kliskey", "r"): 'Robert Kliskey',
("Hillsborough", "16", "Stefanik", "r"): 'Steven Stefanik',
("Hillsborough", "16", "Query", "d"): 'Joshua Query',
("Hillsborough", "17", "Hamer", "d"): 'Heidi Hamer',
("Hillsborough", "17", "Smith", "d"): 'Timothy Smith',
("Hillsborough", "17", "Simmons", "r"): 'Tammy Simmons',
("Hillsborough", "17", "Garthwaite", "r"): 'Dan Garthwaite',
("Hillsborough", "18", "Cornell", "d"): 'Patricia Cornell',
("Hillsborough", "18", "Chicoine", "r"): 'Brian Chicoine',
("Hillsborough", "18", "Griffith", "d"): 'Willis Griffith',
("Hillsborough", "18", "LeClear-Ping", "r"): 'Brittany LeClear-Ping',
("Hillsborough", "19", "Zackeroff", "d"): 'William Zackeroff',
("Hillsborough", "19", "Marston", "r"): 'Dick Marston',
("Hillsborough", "19", "Whitlock", "r"): 'Matt Whitlock',
("Hillsborough", "19", "Snow", "d"): 'Kendall Snow',
("Hillsborough", "2", "Cushman", "r"): 'Lean Cushman',
("Hillsborough", "2", "Hopper", "r"): 'Gary Hopper',
("Hillsborough", "2", "Girard", "d"): 'Robert Girard',
("Hillsborough", "2", "Erf", "r"): 'Keith Erf',
("Hillsborough", "2", "Paveglio", "d"): 'Jennifer Paveglio',
("Hillsborough", "2", "Cisto", "d"): 'Rachel Cisto',
("Hillsborough", "20", "Fordey", "d"): 'Nikki Fordey',
("Hillsborough", "20", "Lascelles", "r"): 'Richard Lascelles',
("Hillsborough", "20", "Boehm", "r"): 'Ralph Boehm',
("Hillsborough", "21", "Notter", "r"): 'Jeanine Notter',
("Hillsborough", "21", "Tausch", "r"): 'Lindsay Tausch',
("Hillsborough", "21", "Balcom", "r"): 'Jack Balcom',
("Hillsborough", "21", "Blasek", "r"): 'Melissa Blasek',
("Hillsborough", "21", "Healey", "r"): 'Bob Healy',
("Hillsborough", "21", "Hinch", "r"): 'Dick Hinch',
("Hillsborough", "21", "Mayville", "r"): 'Mary Mayville',
("Hillsborough", "21", "Mooney", "r"): 'Maureen Mooney',
("Hillsborough", "21", "Sylvester", "d"): 'Joseph Sylvester',
("Hillsborough", "21", "Thomas", "d"): 'Wendy Thomas',
("Hillsborough", "21", "M. Murphy", "d"): 'Mackenzie Murphy',
("Hillsborough", "21", "N. Murphy", "d"): 'Nancy Murphy',
("Hillsborough", "21", "Parente", "d"): 'Cynthia Parente',
("Hillsborough", "21", "Rung", "d"): 'Rosemarie Rung',
("Hillsborough", "21", "B. Stack", "d"): 'Bryce Stack',
("Hillsborough", "21", "K. Stack", "d"): 'Kathryn Stack',
("Hillsborough", "22", "Hansen", "r"): 'Peter Hansen',
("Hillsborough", "22", "Pray", "r"): 'Danielle Pray',
("Hillsborough", "22", "Labranche", "d"): 'Tony Labranche',
("Hillsborough", "22", "Coughlin", "r"): 'Pamela Coughlin',
("Hillsborough", "22", "Murray", "d"): 'Megan Murray',
("Hillsborough", "22", "Veilleux", "d"): 'Daniel Veilleux',
("Hillsborough", "23", "Sheehan", "r"): 'Vanessa Sheehan',
("Hillsborough", "23", "Petrigno", "d"): 'Peter Petrigno',
("Hillsborough", "23", "Perez", "d"): 'Maria Perez',
("Hillsborough", "23", "Thornton", "r"): 'Michael Thornton',
("Hillsborough", "23", "Lloyd", "d"): 'Alexander Lloyd',
("Hillsborough", "23", "Salmon", "d"): 'Herb Salmon',
("Hillsborough", "23", "King", "r"): 'Bill King',
("Hillsborough", "23", "Tourangeau", "r"): 'Steve Tourangeau',
("Hillsborough", "24", "Vann", "d"): 'Ivy Vann',
("Hillsborough", "24", "Pilcher", "r"): 'David Pilcher',
("Hillsborough", "24", "Leishman", "d"): 'Peter Leishman',
("Hillsborough", "24", "Maidment", "r"): 'Christopher Maidment',
("Hillsborough", "25", "Kelley", "r"): 'Diane Kelley',
("Hillsborough", "25", "Somero", "r"): 'Paul Somero',
("Hillsborough", "25", "Lynch", "d"): 'Laura Lynch',
("Hillsborough", "25", "Crooker", "d"): 'Elizabeth Crooker',
("Hillsborough", "26", "Pauer", "r"): 'Diane Pauer',
("Hillsborough", "26", "Wheeler", "d"): 'Chris Wheeler',
("Hillsborough", "26", "Rater", "d"): 'Brian Rater',
("Hillsborough", "26", "Lewicke", "r"): 'John Lewicke',
("Hillsborough", "27", "Werner", "r"): 'David Werner',
("Hillsborough", "27", "Harris", "d"): 'Tom Harris',
("Hillsborough", "27", "McGhee", "d"): 'Kat McGhee',
("Hillsborough", "27", "Homola", "r"): 'Susan Homola',
("Hillsborough", "28", "Lanzara", "r"): 'Tom Lanzara',
("Hillsborough", "28", "Russell", "r"): 'Rosemary Russell',
("Hillsborough", "28", "Ferreira", "r"): 'Elizabeth Ferreira',
("Hillsborough", "28", "Cohen", "d"): 'Bruce Cohen',