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How do you filter rows in a Pandas DataFrame based on a condition?

How do you create a Pandas DataFrame?

pd.create_dataframe({'col1': [1, 2, 3]})

pd.create_df([1, 2, 3])

pd.DataFrame([1, 2, 3])

pd.DataFrame({'col1': [1, 2, 3]})

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How do you perform aggregation after using the "groupby()" function?

What is the purpose of the "pivot_table()" function in Pandas?

It creates a new DataFrame with aggregated values

100%

It reshapes a DataFrame based on a specified column

It calculates the correlation between columns

It creates a summary table from a DataFrame

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What is the purpose of the "duplicated()" function in Pandas?

It checks if a column contains duplicate values

It finds the duplicate rows in a DataFrame

100%

It removes duplicate values from a column

It drops duplicate rows from a DataFrame

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How do you handle missing values in a Pandas DataFrame?

Interpolate missing values

All of the above

Replace missing values with a specific value

Remove rows with missing values

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What is the purpose of the "shape" attribute in a Pandas DataFrame?

It returns the number of rows and columns in a DataFrame

100%

It returns the data types of columns in a DataFrame

It returns the total number of elements in a DataFrame

It returns the number of columns in a DataFrame

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How do you read a CSV file into a Pandas DataFrame?

load_dataframe('file.csv')

pd.read_csv('file.csv')

readcsv('file.csv')

pd.load_csv('file.csv')

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How do you select multiple columns in a Pandas DataFrame?

df['col1', 'col2']

df[['col1', 'col2']]

100%

df.select_columns(['col1', 'col2'])

df.get_columns(['col1', 'col2'])

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How do you drop a column from a Pandas DataFrame?

df.remove_column('column_name')

df.remove(['column_name'], axis=1)

df.drop(['column_name'], axis=1)

df.drop_column('column_name')

100%

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