How can I read only the header column of a CSV file using Python?

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I am looking for a a way to read just the header row of a large number of large CSV files.

Using Pandas, I have this method available, for each csv file:

>>> df = pd.read_csv(PATH_TO_CSV)
>>> df.columns

I could do this with just the csv module:

>>> reader = csv.DictReader(open(PATH_TO_CSV))
>>> reader.fieldnames

The problem with these is that each CSV file is 500MB+ in size, and it seems to be a gigantic waste to read in the entire file of each just to pull the header lines.

My end goal of all of this is to pull out unique column names. I can do that once I have a list of column headers that are in each of these files.

How can I extract only the header row of a CSV file, quickly?


I've used iglob as an example to search for the .csv files, but one way is to use a set, then adjust as necessary, eg:

import csv
from glob import iglob

unique_headers = set()
for filename in iglob('*.csv'):
    with open(filename, 'rb') as fin:
        csvin = csv.reader(fin)
        unique_headers.update(next(csvin, []))

How to read specific column from CSV file in Python, How do I read a csv file without header in Python? You could check if file is already exists and then don't call writeheader() since you're opening the file with an append option. Something like that: import os.path file_exists = os.path.isfile(filename) with open (filename, 'a') as csvfile: headers = ['TimeStamp', 'light', 'Proximity'] writer = csv.DictWriter(csvfile, delimiter=',', lineterminator=' ',fieldnames=headers) if not file_exists


Here's one way. You get 1 row.

In [9]: DataFrame(np.random.randn(10,4),columns=list('abcd')).to_csv('test.csv',mode='w')

In [10]: read_csv('test.csv',index_col=0,nrows=1)
Out[10]: 
          a         b         c         d
0  0.365453  0.633631 -1.917368 -1.996505

Reading column names alone in a csv file, How do you make a column read only in Python? Python has another method for reading csv files – DictReader. As the name suggest, the result will be read as a dictionary, using the header row as keys and other rows as a values. For example this: import csv with open ("actors.csv") as f: reader = csv.DictReader (f) data = [r for r in reader] Will result in a data dict looking as follows:


I might be a little late to the party but here's one way to do it using just the Python standard library. When dealing with text data, I prefer to use Python 3 because unicode. So this is very close to your original suggestion except I'm only reading in one row rather than the whole file.

import csv    

with open(fpath, 'r') as infile:
    reader = csv.DictReader(infile)
    fieldnames = reader.fieldnames

Hopefully that helps!

reading only header row to help map data types to file headers , How do I read a specific column in a CSV file in Python? It is the equivalent of a 5 rows by 11 columns array or matrix, or vector. I have been attempting to read in the csv using various methods I have found here and other places (e.g. python.org) so that it preserves the relationship between columns and rows, where the first row and the first column = non-numerical values.


What about:

pandas.read_csv(PATH_TO_CSV, nrows=1).columns

That'll read the first row only and return the columns found.

15 ways to read CSV file with pandas, How do I convert a CSV file to a list in Python? 7 Answers 7. You can read the header by using the next() function which return the next row of the reader’s iterable object as a list. then you can add the content of the file to a list. Now i has the column's names as a list. Also note that reader.next() does not work in python 3.


Expanding on the answer given by Jeff It is now possbile to use pandas without actually reading any rows.

In [1]: import pandas as pd
In [2]: import numpy as np
In [3]: pd.DataFrame(np.random.randn(10, 4), columns=list('abcd')).to_csv('test.csv', mode='w')

In [4]: pd.read_csv('test.csv', index_col=0, nrows=0).columns.tolist()
Out[4]: ['a', 'b', 'c', 'd']

pandas can have the advantage that it deals more gracefully with CSV encodings.

14.1. csv — CSV File Reading and Writing, You can read the header by using the next() function which return the next row of the reader's iterable object as a list. then you can add the content of the file to a list. Reading CSV Files With csv. Reading from a CSV file is done using the reader object. The CSV file is opened as a text file with Python’s built-in open() function, which returns a file object. This is then passed to the reader, which does the heavy lifting. Here’s the employee_birthday.txt file:


Python: Read a CSV file line by line with or without header , The reason I am proposing this is that I generally have to read in files could be built to only read in the header column of a text or excel file. in order to create a dictionary to set as the dtype arguement in read_csv to be:. The first line of the CSV file represents the header containing a list of column names in the file. The header is optional but highly recommended. The CSV file is commonly used to represent tabular data. For example, consider the following table: The above table can be represented using CSV format as follows:


Python, This tutorial explains how to read a CSV file in python using read_csv function of Example 1 : Read CSV file with header row; Example 2 : Read CSV file with 11 : Read only specific columns; Example 12 : Read some rows and columns  Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Code #1 : read_csv is an important pandas function to read csv files and do operations on it. Opening a CSV file through this is easy.


pandas.read_csv, Each row read from the csv file is returned as a list of strings. in CSV format) and return True if the first row appears to be a series of column headers. Instructs writer objects to only quote those fields which contain special characters such  The csv module’s reader and writer objects read and write sequences. Programmers can also read and write data in dictionary form using the DictReader and DictWriter classes. PEP 305 - CSV File API. The Python Enhancement Proposal which proposed this addition to Python. 13.1.1. Module Contents ¶ The csv module defines the following functions: