Answers for "handle nan in pandas"

dataframe find nan rows

df[df.isnull().any(axis=1)]

count nan pandas

#Python, pandas
#Count missing values for each column of the dataframe df

df.isnull().sum()

find nan values in a column pandas

df['your column name'].isnull().values.any()

pandas nan values in column

df['your column name'].isnull()

handling missing dvalues denoted by a '?' in pandas

# Making a list of missing value typesmissing_values = ["n/a", "na", "--"]df = pd.read_csv("property data.csv", na_values = missing_values)