Reading rows from a CSV file in Python

Question

I have a CSV file, here is a sample of what it looks like:

Year:  Dec: Jan:
1      50   60
2      25   50
3      30   30
4      40   20
5      10   10


        

Answer 1

You could do something like this:

with open("data1.txt") as f:
    lis = [line.split() for line in f]        # create a list of lists
    for i, x in enumerate(lis):              #print the list items 
        print "line{0} = {1}".format(i, x)

# output 
line0 = ['Year:', 'Dec:', 'Jan:']
line1 = ['1', '50', '60']
line2 = ['2', '25', '50']
line3 = ['3', '30', '30']
line4 = ['4', '40', '20']
line5 = ['5', '10', '10']

or :

with open("data1.txt") as f:
    for i, line in enumerate(f):             
        print "line {0} = {1}".format(i, line.split())

# output         
line 0 = ['Year:', 'Dec:', 'Jan:']
line 1 = ['1', '50', '60']
line 2 = ['2', '25', '50']
line 3 = ['3', '30', '30']
line 4 = ['4', '40', '20']
line 5 = ['5', '10', '10']

Edit:

with open('data1.txt') as f:
    print "{0}".format(f.readline().split())
    for x in f:
        x = x.split()
        print "{0} = {1}".format(x[0],sum(map(int, x[1:])))

# output          
['Year:', 'Dec:', 'Jan:']
1 = 110
2 = 75
3 = 60
4 = 60
5 = 20

Answer 2

Reading it columnwise is harder?

Anyway this reads the line and stores the values in a list:

for line in open("csvfile.csv"):
    csv_row = line.split() #returns a list ["1","50","60"]

---

Modern solution:

# pip install pandas
import pandas as pd 
df = pd.read_table("csvfile.csv", sep=" ")

Answer 3

Use the csv module:

import csv

with open("test.csv", "r") as f:
    reader = csv.reader(f, delimiter="\t")
    for i, line in enumerate(reader):
        print 'line[{}] = {}'.format(i, line)

Output:

line[0] = ['Year:', 'Dec:', 'Jan:']
line[1] = ['1', '50', '60']
line[2] = ['2', '25', '50']
line[3] = ['3', '30', '30']
line[4] = ['4', '40', '20']
line[5] = ['5', '10', '10']

Answer 4

Example:

import pandas as pd

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

# read row line by line
for d in data.values:
  # read column by index
  print(d[2])

Answer 5

The Easiest way is this way :

from csv import reader

# open file in read mode
with open('file.csv', 'r') as read_obj:
    # pass the file object to reader() to get the reader object
    csv_reader = reader(read_obj)
    # Iterate over each row in the csv using reader object
    for row in csv_reader:
        # row variable is a list that represents a row in csv
        print(row)

output:
['Year:', 'Dec:', 'Jan:']
['1', '50', '60']
['2', '25', '50']
['3', '30', '30']
['4', '40', '20']
['5', '10', '10']

Answer 6

The csv module handles csv files by row. If you want to handle it by column, pandas is a good solution.

Besides, there are 2 ways to get all (or specific) columns with pure simple Python code.

1. csv.DictReader

with open('demo.csv') as file:
    data = {}
    for row in csv.DictReader(file):
        for key, value in row.items():
            if key not in data:
                data[key] = []
            data[key].append(value)

It is easy to understand.

2. csv.reader with zip

with open('demo.csv') as file:
    data = {values[0]: values[1:] for values in zip(*csv.reader(file))}

This is not very clear, but efficient.

zip(x, y, z) transpose (x, y, z), while x, y, z are lists. *csv.reader(file) make (x, y, z) for zip, with column names.

Demo Result

The content of demo.csv:

a,b,c
1,2,3
4,5,6
7,8,9

The result of 1:

>>> print(data)
{'c': ['3', '6', '9'], 'b': ['2', '5', '8'], 'a': ['1', '4', '7']}

The result of 2:

>>> print(data)
{'c': ('3', '6', '9'), 'b': ('2', '5', '8'), 'a': ('1', '4', '7')}