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Python Regex: The 5 Exclusive Examples

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 Regular expressions (regex) are powerful tools for pattern matching and text manipulation in Python. Here are five Python regex examples with explanations: 01 Matching a Simple Pattern import re text = "Hello, World!" pattern = r"Hello" result = re.search(pattern, text) if result:     print("Pattern found:", result.group()) Output: Output: Pattern found: Hello This example searches for the pattern "Hello" in the text and prints it when found. 02 Matching Multiple Patterns import re text = "The quick brown fox jumps over the lazy dog." patterns = [r"fox", r"dog"] for pattern in patterns:     if re.search(pattern, text):         print(f"Pattern '{pattern}' found.") Output: Pattern 'fox' found. Pattern 'dog' found. It searches for both "fox" and "dog" patterns in the text and prints when they are found. 03 Matching Any Digit   import re text = "The price of the
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How to Read CSV file Data in Python

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Here is a way to read CSV files in Python pandas. The packages you need to import are numpy and pandas. On the flip side, for Text files, you don't need to import these special libraries since python by default support it.



pandas read_csv


Python pandas read_csv


>>> import numpy as np
>>> import pandas as pd


To see how pandas handle this kind of data, we'll create a small CSV file in the working directory as ch05_01.csv.

white, red, blue, green, animal
1,5,2,3,cat 
2,7,8,5,dog 
3,3,6,7,horse 
2,2,8,3,duck 
4,4,2,1,mouse


Since this file is comma-delimited, you can use the read_csv() function to read its content and convert it to a dataframe object.
>>> csvframe = pd.read_csv('ch05_01.csv')
>>> csvframe
   white  red  blue  green animal
0      1    5     2      3    cat
1      2    7     8      5    dog
2      3    3     6      7  horse
3      2    2     8      3   duck
4      4    4     2      1  mouse


Python reading text files


Since python supports text files, you don't need to import NumPy and Pandas. The syntax is a little different. 

Using the Open method, here file is opened with read mode. In the place file name, it has given; the full path of the file. The Print method displays contents. Here read method is used to read the file.

# Open our file in read mode 
f = open("data/flatland01.txt", mode="r") 
# Read and display the text file 
print(f.read())
# Close our file resource 
f.close()

Finally, working with CSV and Text files knowing is helpful for interviews.


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