Module - 11
Data Engineering with Python
,Handling missing data
What is null’s in our dataset
Sometimes our dataset contain empty values in the cell and those cell we
call as null valued cells.
What is the need to handle these null data:
Because we can’t provide these null values to our ML model
,Possible ways to handle null data
● Fill null value with some other value
● Drop null valued rows
, Lets import data and library
Line1: Import pandas
Line 2: read dataframe
Line 3: Get the shape of dataframe
Line 4: Check null value in the True and False form
Line 5: Check null values across columns
Line 6: Check null values for entire dataframe
Data Engineering with Python
,Handling missing data
What is null’s in our dataset
Sometimes our dataset contain empty values in the cell and those cell we
call as null valued cells.
What is the need to handle these null data:
Because we can’t provide these null values to our ML model
,Possible ways to handle null data
● Fill null value with some other value
● Drop null valued rows
, Lets import data and library
Line1: Import pandas
Line 2: read dataframe
Line 3: Get the shape of dataframe
Line 4: Check null value in the True and False form
Line 5: Check null values across columns
Line 6: Check null values for entire dataframe
