### Identifying Missing Values in a DataFrameIn the context of data manipulation and analysis, it is crucial to identify and handle missing values appropriately. Below is an example of a DataFrame and an exercise aimed at understanding how to detect missing values in a specified column.#### DataFrame ExampleGiven the DataFrame (df) as shown in the table below:| X | Y | Z ||-----|-----|---|| 1 | NaN | 1 || 2 | NaN | 2 || NaN | 1 | 3 |#### ExerciseDetermine the output for the following command:```pythondf['Z'].isna()```#### Options1. ``` 0 False 1 False 2 False Name: z, dtype: bool ```2. ``` x 2 y 1 z 3 ```3. ``` x True y True z False dtype: bool ```4. Syntax Error### Explanation of the CommandThe command `df['Z'].isna()` is used to check for missing values (NaN) in the 'Z' column of the DataFrame. The `.isna()` function returns a series of boolean values where `True` indicates the presence of a NaN value and `False` indicates a non-NaN value.Based on the provided DataFrame, there are no NaN values in column 'Z'. Therefore, the output of the command will be:``` 0 False1 False2 FalseName: z, dtype: bool```Thus, the correct option is **1**.

isna() is the function used to detect missing values in the data frame

For the following dataframe (df): 1 NaN 1 2 NaN NaN 1 3 What will be the output for the following command? df['z'].isna) 0 False 1 False 2 False Name: z, dtype: bool 2 y 1 3 X True y True False dtype: bool Syntax Error

For the following dataframe (df): 1 NaN 1 2 NaN NaN 1 3 What will be the output for the following command? df['z'].isna) 0 False 1 False 2 False Name: z, dtype: bool 2 y 1 3 X True y True False dtype: bool Syntax Error

Computer Networking: A Top-Down Approach (7th Edition)

7th Edition

ISBN:9780133594140

Author:James Kurose, Keith Ross

Publisher:James Kurose, Keith Ross

Chapter1: Computer Networks And The Internet

Section: Chapter Questions

Problem R1RQ: What is the difference between a host and an end system? List several different types of end...

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