CODEWITHSUNDEEP
pythonfiledictionary
user3062260
user3062260

Reputation: 1644

read file into a dictionary so that columns become keys and values, Python

I have a data file in the following format:

 9, 12, 16, ABC, a12d
 8, 09, 24, ADP, v154a
 6, 07, 16, ADP, l28a
 2, 14, 15, CDE, d123p

I need to build a dictionary of sets in the following format:

 ABC : ([a12d])
 ADP : ([v154a, l128a])
 CDE : ([d123p])

I can build a set of any of the columns eg:

with open('data.csv','r') as r:
    name = set([line.strip().split(',')[3] for line in r])

I figure there must be a way to make every element in the set into a dictionary key and its adjacent value add to a set? There is an added complication that some of the keys have a multiple values (for example lines 2 and 3 above) but they are separated with into separate lines.

Thanks in advance for any help

Upvotes: 1

Views: 1215

Answers (3)

Harshitha K M
Harshitha K M

Reputation: 1

Here is the below code to read column values and then convert them to the dictionary in python

cat dictionary.txt (This txt has info about Name Age Birthyear)
Luffy    20    2000
Nami     18    2002
Chopper  10    

##################### code is here #######
#!/usr/bin/python3.7.4

d = {} 
with open("dictionary.txt") as f:
    for line in f:
        line=line.split()
        d.setdefault(line[0],[]).append(line[1])
        if len(line)==3:
           d.setdefault(line[0],[]).append(line[2])
        else:
           d.setdefault(line[0],[]).append('NULL') 
print(d)

Output: {'Luffy': ['20', '2000'], 'Nami': ['18', '2002'], 'Chopper': ['10', 'NULL']}

Upvotes: 0

jrjc
jrjc

Reputation: 21883

If you don't mind using pandas:

import pandas as pd

df = pd.read_csv("data.csv", header=None, usecols=[3,4], index_col=0, skipinitialspace=1, names=["key", "value"])

Which can be read as read data.csv, which contain no header, use only columns 3 and 4, and use column 0 (formerly 3) as the index. Skip the initial space in the values, and name the column you read (3 and 4) key and value. This will give you:

df 
     value
key       
ABC   a12d
ADP  v154a
ADP   l28a
CDE  d123p

So you can access any value with .loc:

df.loc["ABC"].values
array(['a12d'], dtype=object)

df.loc["ADP"].values
array([['v154a'],
       ['l28a']], dtype=object)

For the latter, you can flatten the array with ravel():

df.loc["ADP"].values.ravel()
array(['v154a', 'l28a'], dtype=object)

So it's not really a dictionary, but it behaves a bit like it, and you can do much more with this kind of object (a pandas Dataframe). Plus you can easily read and write csv files. If you don't know pandas, have a look :

Upvotes: 1

Delgan
Delgan

Reputation: 19677

from collections import defaultdict

d = defaultdict(set)

with open('data.csv','r') as r:
    for line in r:
        splitted = line.strip().split(',')
        name = splitted[3].strip()
        value = splitted[4].strip()
        d[name].add(value)

Upvotes: 2

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