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Description
SEPARADOR COTTLE DE 2 GARFIOS, GARFIO IZQUIERDO ROMO.
IMSS product code
535.814.6867.01
Each circle represents one of the 15 purchases of SEPARADORES made by the IMSS between 2009 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Aguascalientes Almacen Delegacional En Aguascalientes | Aguascalientes | 2 | 11,410.5 MXN | 3,082.4 MXN | 37 % | 1.48 | 16 de julio de 2009 |
| Delegación San Luis Potosí Almacen Delegacional En San Luis Potosi | San Luis Potosi | 2 | 1,866.2 MXN | 180 MXN | 8 % | 0.32 | 24 de julio de 2018 |
| Delegación Zacatecas Almacen Delegacional En Zacatecas | Zacatecas | 2 | 1,386.2 MXN | 191.2 MXN | 16 % | 0.48 | 6 de julio de 2017 |
| Delegación Coahuila Almacen Delegacional En Coahuila | Coahuila | 1 | 1,252.8 MXN | 403.1 MXN | 47.4 % | 0.949 | 4 de noviembre de 2015 |
| Delegación Colima Almacen Delegacional En Colima | Colima | 1 | 2,912.8 MXN | 401.8 MXN | 16 % | 0.64 | 22 de diciembre de 2011 |
| Delegación Estado de México Oriente Almacen Delegacional En Estado De Mexico Oriente | Estado de México | 1 | 6,351.1 MXN | 2,850 MXN | 81.4 % | 2.44 | 16 de julio de 2012 |
| Delegación Estado de México Poniente Almacen Delegacional En El Estado De Mexico Poniente | Estado de México | 1 | 939.6 MXN | 129.6 MXN | 16 % | 0.32 | 6 de junio de 2014 |
| Delegación Guanajuato Almacen Delegacional En Guanajuato | Guanajuato | 1 | 5,428.8 MXN | 330.8 MXN | 6.49 % | 0.779 | 6 de julio de 2015 |
| Delegación Hidalgo Almacen Delegacional En Hidalgo | Hidalgo | 1 | 988.5 MXN | - MXN | - | - | 6 de agosto de 2015 |
| Delegación Jalisco Almacen Delegacional En Jalisco | Jalisco | 1 | 1,148.4 MXN | 158.4 MXN | 16 % | 0.32 | 13 de julio de 2010 |
| Delegación Tamaulipas Almacen Delegacional En Tamaulipas | Tamaulipas | 1 | 417.6 MXN | - MXN | - | - | 26 de abril de 2012 |
| Delegación Veracruz Sur Almacen Delegacional En Veracruz Sur | Veracruz | 1 | 2,186.1 MXN | 1,336.4 MXN | 157.3 % | 3.15 | 30 de octubre de 2015 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| QUIRURGICA ORTOPEDICA, S. A. DE C. V. | 8 | 1,234.7 MXN | 14.7 % | 2.85 | 2009 - 2018 |
| DEWIMED, S. A. | 2 | 3,578.4 MXN | 105.6 % | 4.22 | 2009 - 2015 |
| BELTRAN SILVA MAURICIO | 1 | 2,850 MXN | 81.4 % | 2.44 | 2012 - 2012 |
| FARMACIA DERMATOLOGICA Y ESPECIALIDADES S.A. DE C. | 1 | 401.8 MXN | 16 % | 0.64 | 2011 - 2011 |
| HEMOST, S. A. DE C. V. | 1 | 158.4 MXN | 16 % | 0.32 | 2010 - 2010 |
| JUAREZ DIAZ MARIA TERESA | 1 | 840.4 MXN | 20.2 % | 0.404 | 2009 - 2009 |
| NEODREN, S. DE R. L. DE C. V. | 1 | - MXN | - | - | 2015 - 2015 |
Date updated in QQW
3 de octubre de 2022
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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=535.814.6867.01")
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=535.814.6867.01')
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=535.814.6867.01')