Creating a dictionary from a csv file?

问题:

I am trying to create a dictionary from a csv file. The first column of the csv file contains unique keys and the second column contains values. Each row of the csv file represents a unique key, value pair within the dictionary. I tried to use the csv.DictReader and csv.DictWriter classes, but I could only figure out how to generate a new dictionary for each row. I want one dictionary. Here is the code I am trying to use:

import csv

with open(\'coors.csv\', mode=\'r\') as infile:
    reader = csv.reader(infile)
    with open(\'coors_new.csv\', mode=\'w\') as outfile:
    writer = csv.writer(outfile)
    for rows in reader:
        k = rows[0]
        v = rows[1]
        mydict = {k:v for k, v in rows}
    print(mydict)

When I run the above code I get a ValueError: too many values to unpack (expected 2). How do I create one dictionary from a csv file? Thanks.

回答1:

I believe the syntax you were looking for is as follows:

with open(\'coors.csv\', mode=\'r\') as infile:
    reader = csv.reader(infile)
    with open(\'coors_new.csv\', mode=\'w\') as outfile:
        writer = csv.writer(outfile)
        mydict = {rows[0]:rows[1] for rows in reader}

Alternately, for python <= 2.7.1, you want:

mydict = dict((rows[0],rows[1]) for rows in reader)

回答2:

import csv
reader = csv.reader(open(\'filename.csv\', \'r\'))
d = {}
for row in reader:
   k, v = row
   d[k] = v

回答3:

Open the file by calling open and then csv.DictReader.

input_file = csv.DictReader(open(\"coors.csv\"))

You may iterate over the rows of the csv file dict reader object by iterating over input_file.

for row in input_file:
    print row

OR To access first line only

dictobj = csv.DictReader(open(\'coors.csv\')).next() 

回答4:

You have to just convert csv.reader to dict:

~ >> cat > 1.csv
key1, value1
key2, value2
key2, value22
key3, value3

~ >> cat > d.py
import csv
with open(\'1.csv\') as f:
    d = dict(filter(None, csv.reader(f)))

print(d)

~ >> python d.py
{\'key3\': \' value3\', \'key2\': \' value22\', \'key1\': \' value1\'}

回答5:

You can also use numpy for this.

from numpy import loadtxt
key_value = loadtxt(\"filename.csv\", delimiter=\",\")
mydict = { k:v for k,v in key_value }

回答6:

This isn\'t elegant but a one line solution using pandas.

import pandas as pd
pd.read_csv(\'coors.csv\', header=None, index_col=0, squeeze=True).to_dict()

If you want to specify dtype for your index (it can\'t be specified in read_csv if you use the index_col argument because of a bug):

import pandas as pd
pd.read_csv(\'coors.csv\', header=None, dtype={0: str}).set_index(0).squeeze().to_dict()

回答7:

I\'d suggest adding if rows in case there is an empty line at the end of the file

import csv
with open(\'coors.csv\', mode=\'r\') as infile:
    reader = csv.reader(infile)
    with open(\'coors_new.csv\', mode=\'w\') as outfile:
        writer = csv.writer(outfile)
        mydict = dict(row[:2] for row in reader if row)

回答8:

If you are OK with using the numpy package, then you can do something like the following:

import numpy as np

lines = np.genfromtxt(\"coors.csv\", delimiter=\",\", dtype=None)
my_dict = dict()
for i in range(len(lines)):
   my_dict[lines[i][0]] = lines[i][1]

回答9:

You can use this, it is pretty cool:

import dataconverters.commas as commas
filename = \'test.csv\'
with open(filename) as f:
      records, metadata = commas.parse(f)
      for row in records:
            print \'this is row in dictionary:\'+rowenter code here

回答10:

One-liner solution

import pandas as pd

dict = {row[0] : row[1] for _, row in pd.read_csv(\"file.csv\").iterrows()}