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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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6 Exclusive List and Tuple Differences in Python

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Here're quick differences between List and Tuple


Here're the quick differences between Tuple and List in Python. These are helpful for interviews and your project.

Tuple and List differences

List

  • Comma-separated elements inside a square bracket [] make a list.
  • The elements are indexed, which starts from '0'
  • These you need to enclose in a single quote and separate by a comma.
  • It can contain another list, which is called a NESTED list.
  • Use type() function to get the type of data it is.
  • The list is mutable (you can change the data). The objects (elements) can be of different data types. Here're examples on the List.

Tuple

  • The elements comma-separated and enclosed in parenthesis () 
  • The elements are indexed, which starts from '0'
  • It can have heterogeneous data (integer, float, string, list, etc.)
  • It is immutable. So you can't change the elements.
  • Use the type() function to get the type of data it is. 
  • Here're examples of Tuple.

List Example

#Illustration of creating a list 
new_list=[1, 2, 3, 4] 
print(new_list) 


# Homogeneous data elements 
new_list1=[1, "John", 55.5] 
print(new_list1) 


# Heterogeneous data elements 
new_list2=[111, [1, "Clara", 75.5]] 
# Nested list 
print(new_list2)


Output



[1, 2, 3, 4]
[1, ‘John’, 55.5]
[111, [1, ‘Clara’, 75.5]]



Tuple Example


#Illustration of unpacking a tuple 
 new_tuple2=(111, [1, "Clara", 75.5], (2, "Simon", 80.5)) 

# Nested tuple 
print(new_tuple2) x, y, z=new_tuple2 
print(x) 
print(y) 
print(z) 


Output



111
[1, ‘Clara’, 75.5]
(2, ‘Simon’, 80.5)

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