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I'm adding the text contained in the second column of a number of csv files into one list to later perform sentiment analysis on each item in the list. My code is fully working for large csv files at the moment, but the sentiment analysis I'm performing on the items in the list takes too long which is why I want to only read the first 200 rows per csv file. The code looks as follows:

import nltk, string, lumpy 
import math
import glob
from collections import defaultdict
columns = defaultdict(list)
from nltk.corpus import stopwords
import math
import sentiment_mod as s
import glob

lijst = glob.glob('21cf/*.csv')

tweets1 = []
for item in lijst:
    stopwords_set = set(stopwords.words("english"))
    with open(item, encoding = 'latin-1') as d:
        reader1=csv.reader(d)
        next(reader1)
        for row in reader1:
            tweets1.extend([row[2]])
        words_cleaned = [" ".join([words for words in sentence.split() if 'http' not in words and not words.startswith('@')]) for sentence in tweets1]
        words_filtered = [e.lower() for e in words_cleaned]
        words_without_stopwords = [word for word in words_filtered if not word in stopwords_set]
    tweets1 = words_without_stopwords
    tweets1 = list(filter(None, tweets1))

How do I make sure to only read over the first 200 rows per csv file with the csv reader?

2
  • Why not simply add a for loop with required range? Commented May 23, 2018 at 13:57
  • You could always just use Pandas like in this question Commented May 23, 2018 at 13:59

3 Answers 3

16

The shortest and most idiomatic way is probably to use itertools.islice:

import itertools
...
        for row in itertools.islice(reader1, 200):
            ...
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Comments

3

You can just add a count, and break when in reaches 200, or add a loop with a range of 200.

Define a variable right before your for loop for rows starts:

count = 0

Then inside your loop:

count = count + 1
if count == 200: 
    break

Comments

3

Pandas is a popular module for manipulating data, like CSVs. Using pandas this is how you could limit the number of rows.

import pandas as pd
# If you only want to read the first 200 (non-header) rows:
pd.read_csv(..., nrows=200)

Comments

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