Given a dataframe dl with columns name, stream and Roll no....

Given a dataframe dl with columns name, stream and Roll no. [CUET 2022] Prabhat wants to print the details of Bhavya' along with stream. Identify the correct statement. (A) print(d1[['name',[stream']] [d]1['name']=-'Bhavya']) (B) $\operatorname{print}(\mathrm{d} 1[[$ 'name', 'stream']] [d['name']==Bhavya') (C) $\operatorname{print}($ d1 $[[$ 'name']=-Bhavya']) (D) $\operatorname{print}(\mathrm{d} 1[[$ 'name','stream'] [d1['name']='Bhavya'])

Given a dataframe dl with columns name, stream and Roll no.
[CUET 2022]
Prabhat wants to print the details of Bhavya' along with stream. Identify the correct statement.
(A) print(d1[['name',[stream']] [d]1['name']=-'Bhavya'])
(B) $\operatorname{print}(\mathrm{d} 1[[$ 'name', 'stream']] [d['name']==Bhavya')
(C) $\operatorname{print}($ d1 $[[$ 'name']=-Bhavya'])
(D) $\operatorname{print}(\mathrm{d} 1[[$ 'name','stream'] [d1['name']='Bhavya'])

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Key Concepts

Pandas DataFrame

A Pandas DataFrame is a two-dimensional, size-mutable, and heterogeneous data structure in Python, which consists of rows and columns similar to a table in a database. It is used for data manipulation, analysis, and cleaning, and supports various operations like filtering, grouping, and joining data.

Boolean Indexing

Boolean indexing is a filtering technique used in Pandas where a boolean expression is applied to a DataFrame to select rows that meet certain conditions. This method evaluates each row with the condition and returns only those rows where the condition evaluates to True, making it an efficient way to subset data based on specific criteria.

Column Selection

Column selection in Pandas involves accessing one or more columns of a DataFrame by specifying their names. This can be done using single brackets for a single column or double brackets for multiple columns, enabling effective extraction or manipulation of specific data fields within the DataFrame.

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