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How to Read a CSV File from Amazon S3 Using Python (With Headers and Rows Displayed)

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  Introduction If you’re working with cloud data, especially on AWS, chances are you’ll encounter data stored in CSV files inside an Amazon S3 bucket . Whether you're building a data pipeline or a quick analysis tool, reading data directly from S3 in Python is a fast, reliable, and scalable way to get started. In this blog post, we’ll walk through: Setting up access to S3 Reading a CSV file using Python and Boto3 Displaying headers and rows Tips to handle larger datasets Let’s jump in! What You’ll Need An AWS account An S3 bucket with a CSV file uploaded AWS credentials (access key and secret key) Python 3.x installed boto3 and pandas libraries installed (you can install them via pip) pip install boto3 pandas Step-by-Step: Read CSV from S3 Let’s say your S3 bucket is named my-data-bucket , and your CSV file is sample-data/employees.csv . ✅ Step 1: Import Required Libraries import boto3 import pandas as pd from io import StringIO boto3 is...
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How to Find Non-word Character: Python Regex Example

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In Python, the regular expression pattern \W matches any non-word character. Here's an example of usage. The valid word characters are [a-zA-Z0-9_]. \W (upper case W) matches any non-word character. Regex examples to find non-word char #1 Example import re text = "Hello, world! How are you today?" non_words = re.findall(r'\W', text) print(non_words) In the above example, the re.findall() function is used to find all non-word characters in the text string using the regular expression pattern \W. The output will be a list of non-word characters found in the string: Output [',', '!', ' ', ' ', '?'] This includes punctuation marks and spaces but excludes letters, digits, and underscores, which are considered word characters in regular expressions. #2 Example import re text = "Hello, world! How are non-word-char:! you today?" non_words = re.findall(r'non-word-char:\W', text) print(non_words) Output ['non-wo...
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