Reputation: 58702
I have a huge file, which has some missing rows. The data needs to be rooted at Country.
The input data is like:
csv_str = """Type,Country,State,County,City,
1,USA,,,
2,USA,OH,,
3,USA,OH,Franklin,
4,USA,OH,Franklin,Columbus
4,USA,OH,Franklin,Springfield
4,USA,WI,Dane,Madison
"""
which needed to be:
csv_str = """Type,Country,State,County,City,
1,USA,,,
2,USA,OH,,
3,USA,OH,Franklin,
4,USA,OH,Franklin,Columbus
4,USA,OH,Franklin,Springfield
4,USA,WI,,
4,USA,WI,Dane,
4,USA,WI,Dane,Madison
"""
The key as per my logic is Type
field, where if I cannot find a County (type 3) for a City (type 4), then insert a row with fields upto County.
Same with County. If I cannot find a State (type 2) for a County (type 3), then insert a row with fields upto State.
With my lack of understanding the facilities in python, I was trying more of a brute-force approach. It is bit problematic as I need lot of iteration over the same file.
I was also tried google-refine, but couldn't get it work. Doing manually is quite error prone.
Any help appreciated.
import csv
import io
csv_str = """Type,Country,State,County,City,
1,USA,,,
2,USA,OH,,
3,USA,OH,Franklin,
4,USA,OH,Franklin,Columbus
4,USA,OH,Franklin,Springfield
4,USA,WI,Dane,Madison
"""
found_county =[]
missing_county =[]
def check_missing_county(row):
found = False
for elm in found_county:
if elm.Type == row.Type:
found = True
if not found:
missing_county.append(row)
print(row)
reader = csv.reader(io.StringIO(csv_str))
for row in reader:
check_missing_county(row)
Upvotes: 0
Views: 107
Reputation: 5604
I've knocked up the following based on my understanding of the question:
import csv
import io
csv_str = u"""Type,Country,State,County,City,
1,USA,,,
2,USA,OH,,
3,USA,OH,Franklin,
4,USA,OH,Franklin,Columbus
4,USA,OH,Franklin,Springfield
4,USA,WI,Dane,Madison
"""
counties = []
states = []
def handle_missing_data(row):
try:
rtype = int(row[0])
except ValueError:
return []
rtype = row[0]
country = row[1]
state = row[2]
county = row[3]
rows = []
# if a state is present and it hasn't a row of it's own
if state and state not in states:
rows.append([rtype, country, state, '', ''])
states.append(state)
# if a county is present and it hasn't a row of it's own
if county and county not in counties:
rows.append([rtype, country, state, county, ''])
counties.append(county)
# if the row hasn't already been added add it now
if row not in rows:
rows.append(row)
return rows
csvf = io.StringIO(csv_str)
reader = csv.reader(csvf)
for row in reader:
new_rows = handle_missing_data(row)
for new_row in new_rows:
print new_row
Upvotes: 1