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Top Questions People Ask About Pandas, NumPy, Matplotlib & Scikit-learn — Answered!

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 Whether you're a beginner or brushing up on your skills, these are the real-world questions Python learners ask most about key libraries in data science. Let’s dive in! 🐍 🐼 Pandas: Data Manipulation Made Easy 1. How do I handle missing data in a DataFrame? df.fillna( 0 ) # Replace NaNs with 0 df.dropna() # Remove rows with NaNs df.isna(). sum () # Count missing values per column 2. How can I merge or join two DataFrames? pd.merge(df1, df2, on= 'id' , how= 'inner' ) # inner, left, right, outer 3. What is the difference between loc[] and iloc[] ? loc[] uses labels (e.g., column names) iloc[] uses integer positions df.loc[ 0 , 'name' ] # label-based df.iloc[ 0 , 1 ] # index-based 4. How do I group data and perform aggregation? df.groupby( 'category' )[ 'sales' ]. sum () 5. How can I convert a column to datetime format? df[ 'date' ] = pd.to_datetime(df[ 'date' ]) ...
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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 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

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