def using_item_id():
df = dr.get_data('train.xls')
item_id = dr.get_unqiue_list(list(df['Item_Id']))
item_id_list = list(dr.get_req_att(df, 'Item_Id'))
item_weight = list(dr.get_req_att(df, 'Item_Weight'))
item_fat_content = list(dr.get_req_att(df, 'Item_Fat_Content'))
item_type = list(dr.get_req_att(df, 'Item_Type'))
for outer_itr in item_id:
for itr in range(len(item_id_list)):
if item_id_list[itr] == outer_itr:
print(item_id_list[itr], item_weight[itr], item_fat_content[itr], item_type[itr])
input()
import dretrive as dr
df = dr.get_data('train.xls')
df = dr.get_req_att(df, ['Item_Type', 'Item_Fat_Content'])
item_list = dr.get_unqiue_list(df['Item_Type'])
print(item_list)
print("Length : ",len(item_list))
item_fat_list = dr.get_unqiue_list(df['Item_Fat_Content'])
print(item_fat_list)
print("Fat types : ", len(item_fat_list))
#fast
import dretrive as dr
import numpy as np
df = dr.get_data('train.xls')
df = dr.get_req_att(df, 'Item_Id')
arr = list(set(df))
item = list(df)
count = np.zeros(len(arr), dtype=int)
for itr in range(len(arr)):
for inner_itr in range(len(item)):
if arr[itr] == item[inner_itr]:
#print(arr[itr])
count[itr] += 1
for itr in range(len(arr)):
print(arr[itr], ' ', count[itr])
import dretrive as dr
import pandas as pd
df = dr.get_data('train.xls')
att_lis = ['Item_Weight', 'Item_Fat_Content', 'Item_Type', 'Outlet_Id', 'Item_Outlet_Sales', 'Item_MRP']
df = dr.get_req_att(df, att_lis)
iweight = list(df['Item_Weight'])
ifat = list(df['Item_Fat_Content'])
itype = list(df['Item_Type'])
shopid = list(df['Outlet_Id'])
sales = list(df['Item_Outlet_Sales'])
mrp = list(df['Item_MRP'])
print('sales error count : ', dr.count_nan(sales))
'''
count_out019 = 0
for itr in range(len(iweight)):
#' ' '
#if (ifat[itr] == 'Low Fat' or ifat[itr] == 'LF' or ifat[itr] == 'low fat') and itype[itr] == 'Baking Goods' and shopid[itr] == 'OUT027' :
# print(iweight[itr], " ", sales[itr], " ", mrp[itr])
#' ' '
if shopid[itr] == 'OUT019':
count_out019 += 1
'''
#print(count_out019)
import dretrive as dr
import dvisual as dv
import pandas as pd
df = dr.get_data('train.xls')
lis = ['Outlet_Id', 'Item_Outlet_Sales']
df = dr.get_req_att(df, lis)
# no empty values
'''
lis = df['Item_Outlet_Sales']
count = 0
for itr in lis:
if pd.isna(itr):
count += 1
print(count)
'''
#no cleaning required
shop_list = df['Outlet_Id']
std_shop_list = dr.get_unqiue_list(shop_list)
sale_list = df['Item_Outlet_Sales']
sales = []
for shop in std_shop_list:
count = 0
for itr in range(len(shop_list)):
if shop == shop_list[itr]:
count += sale_list[itr]
sales.append(count)
if item_fat_content[itr] == "Low Fat" or item_fat_content[
itr] == "low fat" or item_fat_content[itr] == "LF":
df.loc[itr, 'Item_Fat_Content'] = "Low Fat"
else:
df.loc[itr, 'Item_Fat_Content'] = "Regular"
return df
#stub
if __name__ == '__main__':
df = dr.get_data('train.xls')
item_id = dr.get_unqiue_list(list(df['Item_Id']))
item_id_list = list(dr.get_req_att(df, 'Item_Id'))
item_weight = list(dr.get_req_att(df, 'Item_Weight'))
print(dr.count_nan(item_weight))
item_fat_content = list(dr.get_req_att(df, 'Item_Fat_Content'))
item_type = list(dr.get_req_att(df, 'Item_Type'))
for outer_itr in item_id:
temp_list = []
for itr in range(len(item_id_list)):
if item_id_list[itr] == outer_itr:
#print(item_id_list[itr], item_weight[itr], item_fat_content[itr], item_type[itr])
temp_list.append(itr)
df = clean_nan(outer_itr, temp_list, item_weight, df)
item_weight = list(df['Item_Weight'])
print(dr.count_nan(item_weight))
