Does csv.DicReader() return a dictionary object?

While I am trying to use csv.DictReader() to transfer a CSV file to a dictionary, like this:

csv.DictReader()

csv_file = open(input_file, "r")
data = csv.DictReader(csv_file)


However, I cannot apply any dictionary methods into data.

data

Thus, I print the type of data.

data

print(type(data))


and find the type is:

<class 'csv.DictReader'>


So does csv.DictReader() really return a dictionary object? How can I get a dictionary object from CSV?

csv.DictReader()

My CSV file looks like this:

[['play', 'weather', 'temperature'], ['yes', 'sunny', '77'], ['no', 'rainny', '60'], ['yes', 'windy', '70'],...]


Actually, I do not have a expected output. I just want to store these value for my further calculation.

Edit (as per comment): The output could be two parts. The first one is the headers of the csv file, such as ['play', 'weather', 'temperature'] . The second one can be this: [['yes', 'sunny', '77'], ['no', 'rainny', '60'], ['yes', 'windy', '70']...]

['play', 'weather', 'temperature']

[['yes', 'sunny', '77'], ['no', 'rainny', '60'], ['yes', 'windy', '70']...]

2 Answers
2

Given your desired output, you do not need to use dict or, consequently, csv.DictReader. Instead, just use csv.reader, which returns an iterator. Then use next and list to extract headers and data respectively:

dict

csv.DictReader

csv.reader

next

list

from io import StringIO
import csv

x = StringIO("""play,weather,temperature
yes,sunny,77
no,rainy,60
yes,windy,70""")

# replace x with open('file.csv', 'r')
with x as fin:
reader = csv.reader(fin)
headers = next(reader) # get headers from first row
data = list(reader) # exhaust iterator from second row onwards


The result is a list of headers, and a list of lists for data:

print(headers)

['play', 'weather', 'temperature']

print(data)

[['yes', 'sunny', '77'],
['no', 'rainy', '60'],
['yes', 'windy', '70']]


If you are willing to use a 3rd party library, Pandas may be a better option as it handles type conversion and indexing more conveniently:

import pandas as pd

df = pd.read_csv('file.csv')


The result is a pd.DataFrame object:

pd.DataFrame

print(df)

play weather temperature
0 yes sunny 77
1 no rainy 60
2 yes windy 70

print(type(df))

<class 'pandas.core.frame.DataFrame'>


DictReader returns a file-like object. It still reads the data from the csv file in one row at a time, but the returned rows are ordered dictionaries instead of lists.

DictReader

If your files is:

play,weather,temperature
yes,sunny,77
no,rainny,60
yes,windy,70


Then you can use DictReader in the following way:

DictReader

with open('path/to/file.csv') as fp:
header = fp.readline().strip().split(',')
dreader = DictReader(fp, header)
data = list(dreader)


In this case, data will be a list of OrderedDict objects with the mapping from the headers to each item in the row.

data

OrderedDict

data
#returns:
[OrderedDict([('play', 'yes'), ('weather', 'sunny'), ('temperature', '77')]),
OrderedDict([('play', 'no'), ('weather', 'rainny'), ('temperature', '60')]),
OrderedDict([('play', 'yes'), ('weather', 'windy'), ('temperature', '70')])]


Thanks for contributing an answer to Stack Overflow!

But avoid …

To learn more, see our tips on writing great answers.

Required, but never shown

Required, but never shown

By clicking "Post Your Answer", you acknowledge that you have read our updated terms of service, privacy policy and cookie policy, and that your continued use of the website is subject to these policies.