I have an if
statement where it checks if the data frame is not empty. The way I do it is the following:
if dataframe.empty: pass else: #do something
But really I need:
if dataframe is not empty: #do something
My question is - is there a method .not_empty()
to achieve this? I also wanted to ask if the second version is better in terms of performance? Otherwise maybe it makes sense for me to leave it as it is i.e. the first version?
To check if DataFrame is empty in Pandas, use pandas. DataFrame. empty attribute. This attribute returns a boolean value of true if this DataFrame is empty, or false if this DataFrame is not empty.
You can use the attribute df. empty to check whether it's empty or not: if df. empty: print('DataFrame is empty!
Using len(df) or len(df. len() is a built-in function in python that gives the length (or the number of items) of a python object. If the length of a pandas dataframe or its index is zero, we can say that the dataframe is empty.
empty attribute checks if the dataframe is empty or not. It return True if the dataframe is empty else it return False .
Just do
if not dataframe.empty: # insert code here
The reason this works is because dataframe.empty
returns True
if dataframe is empty. To invert this, we can use the negation operator not
, which flips True
to False
and vice-versa.
.empty returns a boolean value
>>> df_empty.empty True
So if not empty can be written as
if not df.empty: #Your code
Check pandas.DataFrame.empty , might help someone.
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