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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' ]) ...

Python Subset: How to Get Subset of Dictionary

Here's a sample program to get the python subset. In this case, you'll find logic for dictionary subsets.


Subset from a Dictionary in Python


Dictionary python

To illustrate, I have taken a dictionary as below with keys and values.

my_first_dict = {

'HP': 100
'IBM': 200
'NTT': 300
'ABC': 400
'GDF': 500
}

I want to make a subset of values greater than 100 and less than 400. How can you achieve this? No worries, below, you will find the logic.


Logic to get subset out of a dictionary

I am using dictionary comprehension to achieve this.

Syntax:


sub_set = { key:value for key, value in my_first_dict.items() value >100 and value <400}


Result

Dictionary comprehension


References

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