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How to Efficiently Import Text Data into Lists or Arrays in Python
When working with text files in Python, it's often convenient to import their contents into structured data structures like lists or arrays for easy analysis and manipulation. However, simply reading lines into a list may not always yield the desired outcome.
Consider the following scenario: a text file containing a comma-separated list of values like this:
0,0,200,0,53,1,0,255,...,0.
The goal is to create a list where each value can be individually accessed. Initial attempts may result in a single list item containing the entire file contents, as seen below:
<code class="python">text_file = open("filename.dat", "r") lines = text_file.readlines() print(lines) print(len(lines)) text_file.close()</code>
Output:
['0,0,200,0,53,1,0,255,...,0.'] 1
To resolve this issue, the string needs to be split into a list of values. The split() method can accomplish this:
<code class="python">lines = text_file.read().split(',')</code>
Alternatively, for a more idiomatic approach, consider using the csv module:
<code class="python">import csv with open('filename.csv', 'r') as fd: reader = csv.reader(fd) for row in reader: # Process each row here</code>
By utilizing these techniques, you can efficiently import text data into lists or arrays in Python, allowing for convenient access and manipulation of individual values.
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