Convert csv to dictionary when csv has no header

python read csv without header
create csv file python
python csv to dictionary header
csv dictionary
csv dictwriter write header
python csv writer header
csv to dictionary python
python csv string to dictionary

I have my data following format in csv file and I want to convert this csv data into dictionary having the first attribute as the key and the rest as values

user115,1,4,8,6
user142,0,2,1,11
user145,0,0,0,3
user148,5,9,22,8
user151,2,7,8,8

Note: In my csv file there is no header line. I have to provide it explicitly.

I tried to convert it using CSV DictReader using following code segment but it is giving me error/ not providing the expected outcome

reader = csv.DictReader(open(file_name),'rb', fieldnames=('key','val1','val2','val3','val4'))

Gives me

TypeError: __init__() got multiple values for argument 'fieldnames'

What is the correct way to do this

Using csv module.

Ex:

import csv
d = {}
with open(filename, "rU") as infile:
    reader = csv.reader(infile)
    for line in reader:
        d[line[0]] = line[1:]
print(d)

Output:

{'user148': ['5', '9', '22', '8'], 'user142': ['0', '2', '1', '11'], 'user145': ['0', '0', '0', '3'], 'user151': ['2', '7', '8', '8'], 'user115': ['1', '4', '8', '6']}

How to read Pandas csv file with no header?, I have a csv file that I am importing in my Python script using pandas. The csv file start value as heading. How to read csv without heading? Create a DictReader object (iterator) by passing file object in csv.DictReader(). Now once we have this DictReader object, which is an iterator. Use this iterator object with for loop to read individual rows of the csv as a dictionary. Where each pair in this dictionary represents contains the column name & column value for that row.

You can do that via pandas

import pandas as pd

d = pd.read_csv(file_name, header=None, index_col=0)
d.T.to_dict("list")

>>> {'user115': [1, 4, 8, 6],
     'user142': [0, 2, 1, 11],
     'user145': [0, 0, 0, 3],
     'user148': [5, 9, 22, 8],
     'user151': [2, 7, 8, 8]}

Python: Read a CSV file line by line with or without header , Python: Read a CSV file line by line with or without header. Varun January from csv import reader. # open file in for each row a dictionary is returned, which contains the pair of column names and cell values for that row. I’m a Network Engineer learning Python, and these are purely my notes. I’m not an expert by any means. Feel free to use any of these examples and improve upon them. Feel free to call me out where things can be done better. I have a CSV full of device-specific variables that I need to use in a script built for generating network device

You can use the csv module and this code snippet

def csv_dict_list(path, fieldnames):
        csv_dict_list = []
        with open(path, 'r') as csv_file:
            reader = csv.DictReader(csv_file, fieldnames = field_names)
            for row in reader:
                csv_dict_list.append(row)
            return csv_dict_list

path = 'YOUR/PATH/HERE/file.csv'

The fieldnames should be a list, like:

field_names = ['Column A', 'Column B', 'Column C', 'Column D', 'Column E']

And then you just call the method

newdict = {}
newdict = csv_dict_list(path, fieldnames)

csv — CSV File Reading and Writing, No automatic data type conversion is performed unless the QUOTE_NONNUMERIC format DictWriter(csvfile, fieldnames=fieldnames) writer.writeheader()  Load DataFrame from CSV with no header If your CSV file does not have a header (column names), you can specify that to read_csv() in two ways. Pass the argument header=None to pandas.read_csv() function. Pass the argument names to pandas.read_csv() function, which implicitly makes header=None.

Simple CSV Data Wrangling with Python, The CSV file has a header row, so we have the field names, but we do have a couple of import csv FUNDING = 'data/funding.csv' def read_funding_data(path​): with and is extremely lightweight because it contains no internal __dict__ . The objects converted from CSV are string values of the original objects that contain property values and no methods. You can use the Export-Csv cmdlet to convert objects to CSV strings. Export-CSV is similar to ConvertTo-CSV, except that it saves the CSV strings to a file.

How to parse csv formatted files using csv.DictReader?, CSV, or "comma-separated values", is a common file format for data. import csv​. Open the file by calling open and then csv.DictReader. input_file When you iterate over a CSV file, each iteration of the loop produces a dictionary from strings to (oldest_person, max_age) else: print "The file does not contain any people. The CSV versions of the objects do not have any methods. You can also use the Export-Csv and Import-Csv cmdlets to convert objects to CSV strings in a file (and back). These cmdlets are the same as the ConvertTo-Csv and ConvertFrom-Csv cmdlets, except that they save the CSV strings in a file.

read_csv – Read a CSV file, This is needed if the CSV does not have a header. key. string. The column name used as a key for the resulting dictionary. If key is unset, the module returns a  I have a .csv file in which each row represents an association between a software application and a web server. My goal is to fetch a List<Server> by application, so I'm mapping the .csv to a Dictionary<string, List<Server>>. I'm using CsvHelper to read the .csv file and map it to objects. .csv format:

Comments
  • Sure you can. Try: reader = csv.DictReader(infile, fieldnames=('key','val1','val2','val3','val4'))