how to check missing values in python pandas code example

Example 1: find nan value in dataframe python

# to mark NaN column as True
df['your column name'].isnull()

Example 2: how to check missing values in python

# Total missing values for each featureprint df.isnull().sum()Out:ST_NUM          2ST_NAME         0OWN_OCCUPIED    2NUM_BEDROOMS    4

Example 3: filling the missing data in pandas

note:to fill a specific value

varable = 1
def fill_mod_acc(most_related_coloum_name,missing_data_coloum):
    if np.isnan(missing_data_coloum):
        return varable[most_related_coloum_name]
    else:
        return missing_data_coloum

df['missing_data_coloum'] = df.apply(lambda x:fill_mod_acc(x['most_related_coloum_name'],x['missing_data_coloum']),axis=1)


Note:to fill mean from existing closley related coloum

varable = df.groupby('most_related_coloum_name').mean()['missing_data_coloum']

def fill_mod_acc(most_related_coloum_name,missing_data_coloum):
    if np.isnan(missing_data_coloum):
        return varable[most_related_coloum_name]
    else:
        return missing_data_coloum

df['missing_data_coloum'] = df.apply(lambda x:fill_mod_acc(x['most_related_coloum_name'],x['missing_data_coloum']),axis=1)