CODEWITHSUNDEEP
pythonpandasdataframe
lunbox
lunbox

Reputation: 363

Create a Python dictionary with start and end values as the keys

What is the best way to translate this into a python dictionary or is there a better way to implement this.

I have a csv file with 3 columns. 1. Start 2. End 3. Value

eg Start, = 10, End = 90 Value = 30 ....Start=10000 End=30000 value =1

I thought I could do 10:30,11:30.....10000:1 for my dictionary, but how can I create this dictionary efficiently using the start and end as the keys.

Upvotes: 0

Views: 341

Answers (3)

westandskif
westandskif

Reputation: 982

Consider checking out convtools library, this provides a lot of data processing primitives (brings code generation though).

from convtools import conversion as c
from convtools.contrib.tables import Table

converter = (
    c.iter({(c.item("Start"), c.item("End")): c.item("Value")})
    .as_type(list)
    .gen_converter()
)

rows = (
    Table.from_csv("input.csv", header=True)
    # cast all columns to int
    .update_all(int)
    # or .update(Start=c.col("Start").as_type(int)) to process one by one
    .into_iter_rows(dict)
)

assert converter(rows) == [{(10, 20): 30}, {(100, 334): 534}, {(122, 3456): 23}]

Upvotes: 0

hpchavaz
hpchavaz

Reputation: 1388

Using the csv lib.

import csv

data = []

with open(filename) as csv_file:
    csv_reader = csv.reader(csv_file)
    for i, row in enumerate(csv_reader):
        if i == 0:  continue # skip header
        data.append({(int(row[0]), int(row[1])): int(row[2])}) # (note)

note: last int could be float depending of requested data type

Upvotes: 0

Yaroslav Kornachevskyi
Yaroslav Kornachevskyi

Reputation: 1218

csv:

Start,End,Value
10,20,30
100,334,534
122,3456,23

Sample:

import pandas as pd
df = pd.read_csv('1.csv')
k = [*zip(df['Start'], df['End'])]
v = list(df['Value'])
d = dict(zip(k, v))
print(d)

Res:

{(10, 20): 30, (100, 334): 534, (122, 3456): 23}

Upvotes: 1

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