лаб 1 / index

import numpy as np
import math
import copy as copy
import pandas as pd
import matplotlib.pyplot as plt

file = pd.ExcelFile('Dataset.xlsx')
df = pd.read_excel(file, sheet_name='Лист1', header=1);

print('DATA FRAME ORIGIN -----------------')
#print(df)

print('DATA FRAME DESCRIBE -----------------')
#print(df.describe())

print('DATA FRAME FILLNA(0) -----------------')
df_1 = df.fillna(0)
#print(df_1)


print('DATA FRAME FILLNA(backfill) -----------------')
df_2 = df.fillna('backfill')
#print(df_2)


print('DATA FRAME FILLNA(bfill) -----------------')
df_3 = df.fillna('bfill')
#print(df_3)


print('DATA FRAME FILLNA(pad) -----------------')
df_4 = df.fillna('pad')
#print(df_4)


print('DATA FRAME FILLNA(ffill) -----------------')
df_5 = df.fillna('ffill')
#print(df_5)

print('DATA FRAME dropna() -----------------')
df_6 = df.dropna()
#print(df_6)

def isNa(value): 
    print(value)
    if isinstance(value, int) or isinstance(value, float):
        if math.isnan(value) and value != 0:
            return True
    return False

def drop_na_20 (df):
    for index, rowObject in df.iterrows():
        countOfNa = 0;
        countOfCols = len(rowObject);
        for key in rowObject:
            if isNa(key):
                countOfNa += 1
        percentNaInRow = (countOfNa / countOfCols) * 100;
        #print('index =', rowObject.name, 'count_na =' ,countOfNa, '|',percentNaInRow, '%')
        if percentNaInRow > 20 or percentNaInRow < 0.1 :
            print('deleting', rowObject.name)
            df = df.drop(rowObject.name)
    return df                
                
df_9 = drop_na_20(df)


df_all_cols = df.dropna();
df_all_cols.loc[0: , 'sum_d'] = 0
df_all_cols.loc[0: , 'countOfCols'] = 0
df_all_rows = df.dropna(axis=1);


def fillNa (df_with_na):
    df_with_na.loc[0: , 'sum_d'] = 0
    df_with_na.loc[0: , 'countOfCols'] = len(df_with_na.columns)
    for label, content in df_with_na.items():
        countOfCols = len(df_with_na.columns);  
        for x in content.index:
            item = df_with_na.loc[x, label];
            d = 0;
            # here nan exist
            if not df_with_na.isna().loc[x, label] and not isinstance(item, str):
                for y, item_1 in enumerate(df_all_cols.loc[:, label]):
                    if label != 'sum_d' and label != 'countOfCols':
                        #print(label, '-----------' ,df_with_na.loc[x, label])
                        df_with_na.loc[x, 'sum_d'] += abs(item_1 - item)
                        #print(label, '-----------' ,df_with_na.loc[x, label])
                    elif label == 'sum_d':
                        df_with_na.loc[x, label] = df_with_na.loc[x, label] / (df_with_na.loc[x, 'countOfCols'] - 1)
            else:
                df_with_na.loc[x, 'countOfCols'] = df_with_na.loc[x, 'countOfCols'] - 1;
                
    
                    
            

fillNa(df_9);
print('succes')