i'd like to import certain columns in this csv into a nested python dict:
Name, Type, ID, Job, Height
Adam, Man, asmith, factory, 5
Ben, Man, bjones, mine, 6
Jamie, Woman, jbarnes, bank, 5.5
output:
dict1 = { asmith: {Name:Adam, Type:Man, Height:5},
bjones, {Name:Ben, Type:Man, Height:6},
jbarnes:, {Name:Jamie,Type:Woman, Height:5.5} }
We can use the DictReader from csv for this:
from csv import DictReader
with open('data.csv') as csvfile:
reader = DictReader(csvfile)
result = {row[' ID'] : row for row in reader}
Now result will be a dictionary that maps IDs to dictionaries. The dictionary will contain the 'ID' as well. Now result will be:
{' bjones': {'Name': 'Ben', ' Type': ' Man', ' Height': ' 6', ' ID': ' bjones', ' Job': ' mine'}, ' jbarnes': {'Name': 'Jamie', ' Type': ' Woman', ' Height': ' 5.5', ' ID': ' jbarnes', ' Job': ' bank'}, ' asmith': {'Name': 'Adam', ' Type': ' Man', ' Height': ' 5', ' ID': ' asmith', ' Job': ' factory'}}
As we can see the values are not stripped: these contain spaces on the left and the right. We can process these as follows:
from csv import DictReader
with open('data.csv') as csvfile:
reader = DictReader(csvfile)
result = {}
for row in reader:
row = {k.strip():v.strip() for k,v in row.items()}
result[row.pop('ID')] = row
This will remove the ID key from the dictionaries as well. Now the answer is:
>>> result
{'jbarnes': {'Name': 'Jamie', 'Height': '5.5', 'Job': 'bank', 'Type': 'Woman'}, 'bjones': {'Name': 'Ben', 'Height': '6', 'Job': 'mine', 'Type': 'Man'}, 'asmith': {'Name': 'Adam', 'Height': '5', 'Job': 'factory', 'Type': 'Man'}}
EDIT: In case you want to ignore the first line, you can call next(..) on the file handler first:
from csv import DictReader
with open('data.csv') as csvfile:
next(csvfile)
reader = DictReader(csvfile)
result = {}
for row in reader:
row = {k.strip():v.strip() for k,v in row.items()}
result[row.pop('ID')] = row
row.pop('ID') to remove it from the dictionary.