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15 Python Tips : How to Write Code Effectively

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 Here are some Python tips to keep in mind that will help you write clean, efficient, and bug-free code.     Python Tips for Effective Coding 1. Code Readability and PEP 8  Always aim for clean and readable code by following PEP 8 guidelines.  Use meaningful variable names, avoid excessively long lines (stick to 79 characters), and organize imports properly. 2. Use List Comprehensions List comprehensions are concise and often faster than regular for-loops. Example: squares = [x**2 for x in range(10)] instead of creating an empty list and appending each square value. 3. Take Advantage of Python’s Built-in Libraries  Libraries like itertools, collections, math, and datetime provide powerful functions and data structures that can simplify your code.   For example, collections.Counter can quickly count elements in a list, and itertools.chain can flatten nested lists. 4. Use enumerate Instead of Range     When you need both the index and the value in a loop, enumerate is a more Pyth
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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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