[python] Reading column names alone in a csv file

I have a csv file with the following columns:

id,name,age,sex

Followed by a lot of values for the above columns. I am trying to read the column names alone and put them inside a list.

I am using Dictreader and this gives out the correct details:

with open('details.csv') as csvfile:
    i=["name","age","sex"]
    re=csv.DictReader(csvfile)
    for row in re:
        for x in i:
            print row[x]

But what I want to do is, I need the list of columns, ("i" in the above case)to be automatically parsed with the input csv than hardcoding them inside a list.

with open('details.csv') as csvfile:
   
    rows=iter(csv.reader(csvfile)).next()
    header=rows[1:]
    re=csv.DictReader(csvfile)
    for row in re:
        print row
        for x in header:
            
            print row[x]

This gives out an error

Keyerrror:'name'

in the line print row[x]. Where am I going wrong? Is it possible to fetch the column names using Dictreader?

This question is related to python

The answer is


I am just mentioning how to get all the column names from a csv file. I am using pandas library.

First we read the file.

import pandas as pd
file = pd.read_csv('details.csv')

Then, in order to just get all the column names as a list from input file use:-

columns = list(file.head(0))

The csv.DictReader object exposes an attribute called fieldnames, and that is what you'd use. Here's example code, followed by input and corresponding output:

import csv
file = "/path/to/file.csv"
with open(file, mode='r', encoding='utf-8') as f:
    reader = csv.DictReader(f, delimiter=',')
    for row in reader:
        print([col + '=' + row[col] for col in reader.fieldnames])

Input file contents:

col0,col1,col2,col3,col4,col5,col6,col7,col8,col9
00,01,02,03,04,05,06,07,08,09
10,11,12,13,14,15,16,17,18,19
20,21,22,23,24,25,26,27,28,29
30,31,32,33,34,35,36,37,38,39
40,41,42,43,44,45,46,47,48,49
50,51,52,53,54,55,56,57,58,59
60,61,62,63,64,65,66,67,68,69
70,71,72,73,74,75,76,77,78,79
80,81,82,83,84,85,86,87,88,89
90,91,92,93,94,95,96,97,98,99

Output of print statements:

['col0=00', 'col1=01', 'col2=02', 'col3=03', 'col4=04', 'col5=05', 'col6=06', 'col7=07', 'col8=08', 'col9=09']
['col0=10', 'col1=11', 'col2=12', 'col3=13', 'col4=14', 'col5=15', 'col6=16', 'col7=17', 'col8=18', 'col9=19']
['col0=20', 'col1=21', 'col2=22', 'col3=23', 'col4=24', 'col5=25', 'col6=26', 'col7=27', 'col8=28', 'col9=29']
['col0=30', 'col1=31', 'col2=32', 'col3=33', 'col4=34', 'col5=35', 'col6=36', 'col7=37', 'col8=38', 'col9=39']
['col0=40', 'col1=41', 'col2=42', 'col3=43', 'col4=44', 'col5=45', 'col6=46', 'col7=47', 'col8=48', 'col9=49']
['col0=50', 'col1=51', 'col2=52', 'col3=53', 'col4=54', 'col5=55', 'col6=56', 'col7=57', 'col8=58', 'col9=59']
['col0=60', 'col1=61', 'col2=62', 'col3=63', 'col4=64', 'col5=65', 'col6=66', 'col7=67', 'col8=68', 'col9=69']
['col0=70', 'col1=71', 'col2=72', 'col3=73', 'col4=74', 'col5=75', 'col6=76', 'col7=77', 'col8=78', 'col9=79']
['col0=80', 'col1=81', 'col2=82', 'col3=83', 'col4=84', 'col5=85', 'col6=86', 'col7=87', 'col8=88', 'col9=89']
['col0=90', 'col1=91', 'col2=92', 'col3=93', 'col4=94', 'col5=95', 'col6=96', 'col7=97', 'col8=98', 'col9=99']

import pandas as pd
data = pd.read_csv("data.csv")
cols = data.columns

Thanking Daniel Jimenez for his perfect solution to fetch column names alone from my csv, I extend his solution to use DictReader so we can iterate over the rows using column names as indexes. Thanks Jimenez.

with open('myfile.csv') as csvfile:

    rest = []
    with open("myfile.csv", "rb") as f:
        reader = csv.reader(f)
        i = reader.next()
        i=i[1:]
        re=csv.DictReader(csvfile)
        for row in re:
            for x in i:
                print row[x]

How about

with open(csv_input_path + file, 'r') as ft:
    header = ft.readline() # read only first line; returns string
    header_list = header.split(',') # returns list

I am assuming your input file is CSV format. If using pandas, it takes more time if the file is big size because it loads the entire data as the dataset.


here is the code to print only the headers or columns of the csv file.

import csv
HEADERS = next(csv.reader(open('filepath.csv')))
print (HEADERS)

Another method with pandas

import pandas as pd
HEADERS = list(pd.read_csv('filepath.csv').head(0))
print (HEADERS)

Though you already have an accepted answer, I figured I'd add this for anyone else interested in a different solution-

An implementation could be as follows:

import csv

with open('C:/mypath/to/csvfile.csv', 'r') as f:
    d_reader = csv.DictReader(f)

    #get fieldnames from DictReader object and store in list
    headers = d_reader.fieldnames

    for line in d_reader:
        #print value in MyCol1 for each row
        print(line['MyCol1'])

In the above, d_reader.fieldnames returns a list of your headers (assuming the headers are in the top row). Which allows...

>>> print(headers)
['MyCol1', 'MyCol2', 'MyCol3']

If your headers are in, say the 2nd row (with the very top row being row 1), you could do as follows:

import csv

with open('C:/mypath/to/csvfile.csv', 'r') as f:
    #you can eat the first line before creating DictReader.
    #if no "fieldnames" param is passed into
    #DictReader object upon creation, DictReader
    #will read the upper-most line as the headers
    f.readline()

    d_reader = csv.DictReader(f)
    headers = d_reader.fieldnames

    for line in d_reader:
        #print value in MyCol1 for each row
        print(line['MyCol1'])

I literally just wanted the first row of my data which are the headers I need and didn't want to iterate over all my data to get them, so I just did this:

with open(data, 'r', newline='') as csvfile:
t = 0
for i in csv.reader(csvfile, delimiter=',', quotechar='|'):
    if t > 0:
        break
    else:
        dbh = i
        t += 1