23. A data analyst is cleaning data in preparation of training a machine learning model. Whilst cleaning the data, she has observed that there are missing values in the data. Which of the following lines of code can she write to find the percentage of missing values in each column? - i. data.isnull().sum(axis = 1) / len(data) * 100- ii. data.isnull().sum(axis = 0) / len(data) * 100- iii. data.isnull().mean(axis = 1) * 100- iv. data.isnull().mean(axis = 0 ) * 100ii. and ivi. and iii.i onlyii. onlyiii. onlyiv. onlyNone of the above
Question
- A data analyst is cleaning data in preparation of training a machine learning model. Whilst cleaning the data, she has observed that there are missing values in the data. Which of the following lines of code can she write to find the percentage of missing values in each column? - i. data.isnull().sum(axis = 1) / len(data) * 100- ii. data.isnull().sum(axis = 0) / len(data) * 100- iii. data.isnull().mean(axis = 1) * 100- iv. data.isnull().mean(axis = 0 ) * 100ii. and ivi. and iii.i onlyii. onlyiii. onlyiv. onlyNone of the above
Solution
The correct answer is "ii. and iv." These lines of code will calculate the percentage of missing values in each column of the data.
Here's why:
-
ii.
data.isnull().sum(axis = 0) / len(data) * 100: This line of code first identifies the null or missing values in the data (data.isnull()), then sums these up for each column (sum(axis = 0)). This sum is then divided by the total number of rows (len(data)) to get the proportion of missing values, which is then multiplied by 100 to convert it into a percentage. -
iv.
data.isnull().mean(axis = 0 ) * 100: This line of code works similarly, but instead of summing the missing values, it calculates the mean. Sinceisnull()returns 1 for missing values and 0 for non-missing values, the mean of these will give the proportion of missing values, which is then converted into a percentage.
The other lines of code (i. and iii.) would calculate the percentage of missing values in each row, not each column, because they use axis = 1.
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