np.nan pandas code example
Example 1: missing values in a dataset python
df.isnull().sum()
Example 2: pandas nan values in column
df['your column name'].isnull()
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: 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)