[python] How to ignore the first line of data when processing CSV data?

I am asking Python to print the minimum number from a column of CSV data, but the top row is the column number, and I don't want Python to take the top row into account. How can I make sure Python ignores the first line?

This is the code so far:

import csv

with open('all16.csv', 'rb') as inf:
    incsv = csv.reader(inf)
    column = 1                
    datatype = float          
    data = (datatype(column) for row in incsv)   
    least_value = min(data)

print least_value

Could you also explain what you are doing, not just give the code? I am very very new to Python and would like to make sure I understand everything.

This question is related to python csv

The answer is


For me the easiest way to go is to use range.

import csv

with open('files/filename.csv') as I:
    reader = csv.reader(I)
    fulllist = list(reader)

# Starting with data skipping header
for item in range(1, len(fulllist)): 
    # Print each row using "item" as the index value
    print (fulllist[item])  

In a similar use case I had to skip annoying lines before the line with my actual column names. This solution worked nicely. Read the file first, then pass the list to csv.DictReader.

with open('all16.csv') as tmp:
    # Skip first line (if any)
    next(tmp, None)

    # {line_num: row}
    data = dict(enumerate(csv.DictReader(tmp)))

Borrowed from python cookbook,
A more concise template code might look like this:

import csv
with open('stocks.csv') as f:
    f_csv = csv.reader(f) 
    headers = next(f_csv) 
    for row in f_csv:
        # Process row ...

To skip the first line just call:

next(inf)

Files in Python are iterators over lines.


You would normally use next(incsv) which advances the iterator one row, so you skip the header. The other (say you wanted to skip 30 rows) would be:

from itertools import islice
for row in islice(incsv, 30, None):
    # process

I would convert csvreader to list, then pop the first element

import csv        

with open(fileName, 'r') as csvfile:
        csvreader = csv.reader(csvfile)
        data = list(csvreader)               # Convert to list
        data.pop(0)                          # Removes the first row

        for row in data:
            print(row)

Because this is related to something I was doing, I'll share here.

What if we're not sure if there's a header and you also don't feel like importing sniffer and other things?

If your task is basic, such as printing or appending to a list or array, you could just use an if statement:

# Let's say there's 4 columns
with open('file.csv') as csvfile:
     csvreader = csv.reader(csvfile)
# read first line
     first_line = next(csvreader)
# My headers were just text. You can use any suitable conditional here
     if len(first_line) == 4:
          array.append(first_line)
# Now we'll just iterate over everything else as usual:
     for row in csvreader:
          array.append(row)

Well, my mini wrapper library would do the job as well.

>>> import pyexcel as pe
>>> data = pe.load('all16.csv', name_columns_by_row=0)
>>> min(data.column[1])

Meanwhile, if you know what header column index one is, for example "Column 1", you can do this instead:

>>> min(data.column["Column 1"])

use csv.DictReader instead of csv.Reader. If the fieldnames parameter is omitted, the values in the first row of the csvfile will be used as field names. you would then be able to access field values using row["1"] etc


The documentation for the Python 3 CSV module provides this example:

with open('example.csv', newline='') as csvfile:
    dialect = csv.Sniffer().sniff(csvfile.read(1024))
    csvfile.seek(0)
    reader = csv.reader(csvfile, dialect)
    # ... process CSV file contents here ...

The Sniffer will try to auto-detect many things about the CSV file. You need to explicitly call its has_header() method to determine whether the file has a header line. If it does, then skip the first row when iterating the CSV rows. You can do it like this:

if sniffer.has_header():
    for header_row in reader:
        break
for data_row in reader:
    # do something with the row

just add [1:]

example below:

data = pd.read_csv("/Users/xyz/Desktop/xyxData/xyz.csv", sep=',', header=None)**[1:]**

that works for me in iPython


I would use tail to get rid of the unwanted first line:

tail -n +2 $INFIL | whatever_script.py 

Python 3.X

Handles UTF8 BOM + HEADER

It was quite frustrating that the csv module could not easily get the header, there is also a bug with the UTF-8 BOM (first char in file). This works for me using only the csv module:

import csv

def read_csv(self, csv_path, delimiter):
    with open(csv_path, newline='', encoding='utf-8') as f:
        # https://bugs.python.org/issue7185
        # Remove UTF8 BOM.
        txt = f.read()[1:]

    # Remove header line.
    header = txt.splitlines()[:1]
    lines = txt.splitlines()[1:]

    # Convert to list.
    csv_rows = list(csv.reader(lines, delimiter=delimiter))

    for row in csv_rows:
        value = row[INDEX_HERE]

The new 'pandas' package might be more relevant than 'csv'. The code below will read a CSV file, by default interpreting the first line as the column header and find the minimum across columns.

import pandas as pd

data = pd.read_csv('all16.csv')
data.min()

Python 2.x

csvreader.next()

Return the next row of the reader’s iterable object as a list, parsed according to the current dialect.

csv_data = csv.reader(open('sample.csv'))
csv_data.next() # skip first row
for row in csv_data:
    print(row) # should print second row

Python 3.x

csvreader.__next__()

Return the next row of the reader’s iterable object as a list (if the object was returned from reader()) or a dict (if it is a DictReader instance), parsed according to the current dialect. Usually you should call this as next(reader).

csv_data = csv.reader(open('sample.csv'))
csv_data.__next__() # skip first row
for row in csv_data:
    print(row) # should print second row

this might be a very old question but with pandas we have a very easy solution

import pandas as pd

data=pd.read_csv('all16.csv',skiprows=1)
data['column'].min()

with skiprows=1 we can skip the first row then we can find the least value using data['column'].min()