find missing values pandas code example

Example 1: count missing values by column in pandas

df.isna().sum()

Example 2: missing values in a dataset python

df.isnull().sum()

Example 3: represent NaN with pandas in python

import pandas as pd

if pd.isnull(float("Nan")):
  print("Null Value.")

Example 4: 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)

Example 5: getting the number of missing values in pandas

cols_to_delete = df.columns[df.isnull().sum()/len(df) > .90]
df.drop(cols_to_delete, axis = 1, inplace = True)