(picture is a snapshot of my df)
I want to remove the rows that have a zero value. I don't want to modify the DataFrame, but create an assignment which reflects the DataFrame with no zero values in the 'amount spent' column.
1 Answer
This syntax can be used to view (index) a DataFrame based on a given condition:
# View whole DataFrame where `amount_spent` is not zero.
df[df['amount_spent'] != 0]
Here is the official pandas documentation on indexing.
What's happening?
The df['amount_spent'] != 0 statement returns a 'mask' as a boolean array (Series), which is then passed into the 'rows parameter index' (if you will) of the overall DataFrame as: df[<masked_array>].
This will create a 'view' of the DataFrame and not alter it in any way.
1 Comment
Stephen
For anybody who finds this but wants to actually change the dataframe, you just assign it:
df = df[df['amount_spent'] != 0]
df[df['amount_spent'] != 0]