mean imputation in python code example
Example 1: list mean python
def Average(lst):
return sum(lst) / len(lst)
lst = [15, 9, 55, 41, 35, 20, 62, 49]
average = Average(lst)
print("Average of the list =", round(average, 2))
Example 2: how to calculate mean in python
import statistics
a = [1,2,3,4,5]
mean = statistics.mean(a)
Example 3: replace missing values, encoded as np.nan, using the mean value of the columns
import numpy as np
from sklearn.impute import SimpleImputer
imp = SimpleImputer(missing_values=np.nan, strategy='mean')
imp.fit([[1, 2], [np.nan, 3], [7, 6]])
X = [[np.nan, 2], [6, np.nan], [7, 6]]
print(imp.transform(X))
import pandas as pd
df = pd.DataFrame([["a", "x"],
[np.nan, "y"],
["a", np.nan],
["b", "y"]], dtype="category")
imp = SimpleImputer(strategy="most_frequent")
print(imp.fit_transform(df))