In Pandas, what happens if there are empty or missing values in a CSV file and we try to read it?
If the CSV file contains missing values, then when we read the file, it will populate the missing cells with
NaN is short of “Not a Number”, and used to signify missing values.
If needed, we can replace these
NaN values with an actual value, like
0 or an empty string
'', using the
fillna() method. Or, we can drop any rows that contain an empty value, using
For example, if we had a CSV file containing the following:
name,flavor,topping ,chocolate,chocolate shavings Birthday Cake,,gold sprinkles
The second row is missing a value in the first column, and the third row is missing a value in the second column.
When we read this file using Pandas
read_csv, it will load it like so, filling in the missing values with
name flavor topping NaN chocolate chocolate shavings Birthday Cake NaN gold sprinkles