Hello,
I want to iterate through a dataframe and check for a null value:
for i, row in df.iterrows():
if row['Some column'] is not null:
Do some stuff!
Thank you
Do you mean None, rather than null?
nan
import numpy as np
df.replace(np.nan, '', regex=True) #this code will replace all the nan (Null) values with an empty string for the entire dataframe
I want to identify a nan value while iterating through rows.
You can use pandas
.isnull() or
.notnull()
if row.notnull()['Some column']:
do something
or
if row[['Some column']].notnull():
do something
(.isnull() or .notnull() are dataframe/series methods, they do not work for single "cell")
You can use check single cell with some function appropriate to a cell type - like
np.isnan() for numerical column or is not None for string field.
Maybe you can avoid iterating with something like
df.isnull().any(axis=1) # gives True for rows with NaN(s)
combined with .apply().