fill missing values in column pandas with mean
df.fillna(df.mean(), inplace=True)
fill missing values in column pandas with mean
df.fillna(df.mean(), inplace=True)
how to fill missing values dataframe with mean
sub2['income'].fillna((sub2['income'].mean()), inplace=True)
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)
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