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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 Access Dictionary Key-Value Data in Python

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Use for-loop to read dictionary data in python. Here's an example of reading dictionary data. It's helpful to use in real projects.


Sample Program to Read Dictionary


Python program to read dictionary data

yearly_revenue = {

   2017 : 1000000,

   2018 : 1200000,

   2019 : 1250000,

   2020 : 1100000,

   2021 : 1300000,

 }

total_income = 0

for year_id in yearly_revenue.keys():

  total_income+=yearly_revenue[year_id]

  print(year_id, yearly_revenue[year_id])


print(total_income)

print(total_income/len(yearly_revenue))


Output


2017 1000000

2018 1200000

2019 1250000

2020 1100000

2021 1300000

5850000

1170000.0



** Process exited - Return Code: 0 **

Press Enter to exit the terminal


Explanation

The input is dictionary data. The total revenue sums up for each year. Notably, the critical point is using the dictionary keys method.


References

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