replace nan in pandas
df['DataFrame Column'] = df['DataFrame Column'].fillna(0)replace nan in pandas
df['DataFrame Column'] = df['DataFrame Column'].fillna(0)pandas replace nan
data["Gender"].fillna("No Gender", inplace = True)replace error with nan pandas
df['workclass'].replace('?', np.NaN)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)Copyright © 2021 Codeinu
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