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

Question

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. Ho

Answer 1

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)))

Answer 2

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

Answer 3

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

tail -n +2 $INFIL | whatever_script.py 

Answer 4

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

Answer 5

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)

Answer 6

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)