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Description
DE 15 CM DE DIAMETRO Y PROFUNDIDAD DE 5 CM.:"MATERIAL DESECHABLE BIODEGRADABLE"
Classification
Artículos de consumo. Articulos de cocina y comedor
IMSS product code
120.864.0480.00
Each circle represents one of the 4 purchases of TAZON made by the IMSS between 2015 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Veracruz Norte Almacen Delegacional En Veracruz Norte | Veracruz | 4 | 64,424.1 MXN | 8,886.1 MXN | 16 % | 6,864.3 | 11 de abril de 2018 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| DISTRIBUIDORA KALA S.A. DE C.V. | 2 | 5,649.6 MXN | 16 % | 4,704 | 2015 - 2016 |
| JARAMILLO ORTIZ VERONICA | 1 | 448.6 MXN | 16 % | 224.3 | 2017 - 2017 |
| RUIZ DUARTE ARELI MIREYA | 1 | 2,787.8 MXN | 16 % | 1,936 | 2018 - 2018 |
Entity type
Articulos de cocina y comedor
Date updated in QQW
3 de octubre de 2022
Source(s)
Part of the project
Organization responsible for the import
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Add this to your code:
library(rjson)
#Read JSON data into R
data <- fromJSON(file="http://localhost:10010/v3/products?limit=1&sort=&embed=true&db_prefix=&id=120.864.0480.00")
Add this to your code:
import json, urllib
#Read JSON data into python
response = urllib2.urlopen('http://localhost:10010/v3/products?limit=1&sort=&embed=true&db_prefix=&id=120.864.0480.00')
data = json.loads(response.read())
Add this to your code:
import pandas as pd
#Read JSON data into pandas
df = pd.read_json('http://localhost:10010/v3/products?limit=1&sort=&embed=true&db_prefix=&id=120.864.0480.00')