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Description
ROSA DE BENGALA COLORANTE --BIOLOGICO TA.
IMSS product code
080.229.0593.01
Each circle represents one of the 27 purchases of REACTIVOS QUÍMICOS made by the IMSS between 2009 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Sur del DF Almacen Delegacional En El D.f. Zona Sur | Ciudad de México | 8 | 59,987.5 MXN | 7,685 MXN | 15.8 % | 11.5 | 18 de enero de 2018 |
| Delegación Sonora Almacen Delegacional En Sonora | Sonora | 4 | 34,135.1 MXN | 5,399.2 MXN | 25.5 % | 9.99 | 11 de marzo de 2014 |
| H. de Especialidades No. 1 Centro Médico Nacional del Bajio, León, Gto. Umae Especialidades Guanajuato | Guanajuato | 3 | 22,645.8 MXN | 2,590.5 MXN | 12.9 % | 4.65 | 1 de enero de 2011 |
| Delegación Estado de México Oriente Almacen Delegacional En Estado De Mexico Oriente | Estado de México | 2 | 4,147.1 MXN | 754.9 MXN | 23 % | 1.34 | 27 de enero de 2010 |
| Delegación Jalisco Almacen Delegacional En Jalisco | Jalisco | 2 | 15,103.8 MXN | 1,597.8 MXN | 11.8 % | 2.83 | 2 de enero de 2010 |
| Delegación Morelos Almacen Delegacional En Morelos | Morelos | 2 | 11,576.8 MXN | 967.5 MXN | 7.39 % | 1.77 | 10 de enero de 2012 |
| Delegación Veracruz Norte Almacen Delegacional En Veracruz Norte | Veracruz | 2 | 17,096.3 MXN | 3,999.9 MXN | 30.3 % | 7.72 | 9 de enero de 2013 |
| Delegación Michoacán Almacen Delegacional En Michoacan | Michoacán | 1 | 14,848 MXN | 2,528 MXN | 20.5 % | 3.28 | 11 de abril de 2017 |
| Delegación Oaxaca Almacen Delegacional En Oaxaca | Oaxaca | 1 | 645.3 MXN | 90.3 MXN | 16.3 % | 0.163 | 1 de enero de 2010 |
| Delegación Puebla Almacen Delegacional En Puebla | Puebla | 1 | 1,201.8 MXN | 60.6 MXN | 5.31 % | 0.106 | 2 de marzo de 2009 |
| Delegación Quintana Roo Almacen Delegacional En Quintana Roo | Quintana Roo | 1 | 800.4 MXN | 245.5 MXN | 44.2 % | 0.442 | 1 de enero de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| DISTRIBUIDORA LAB-HOS, S.A. DE C.V. | 8 | 7,187.2 MXN | 18.1 % | 13.6 | 2009 - 2014 |
| CONTROL TECNICO Y REPRESENTACIONES, S. A. DE C. V. | 6 | 4,156.6 MXN | 25.7 % | 7.48 | 2009 - 2011 |
| FCD LABS, S.A. DE C.V. | 5 | 2,663.5 MXN | 11.9 % | 4.83 | 2009 - 2015 |
| CASLAB DE MEXICO, S. A. DE C. V. | 3 | 6,771.2 MXN | 16.5 % | 8.32 | 2017 - 2018 |
| CIENTIFICA Y SALUD S.A. DE C.V. | 1 | 2,217.9 MXN | 13.1 % | 4.33 | 2014 - 2014 |
| DISTRIBUCION Y MANTENIMIENTO DEL NOROESTE SA DE CV | 1 | 1,658 MXN | 24.2 % | 2.91 | 2009 - 2009 |
| IMPULSORA MEDICA, S. A. DE C. V. | 1 | 277.5 MXN | 25 % | 0.5 | 2010 - 2010 |
| INTERACTIVOS PARA LABORATORIO S.A. DE C.V. | 1 | 509.7 MXN | 7.65 % | 0.919 | 2010 - 2010 |
| METRIX LABORATORIOS, S.A. DE C.V. | 1 | 477.4 MXN | 20.9 % | 0.837 | 2009 - 2009 |
Date updated in QQW
3 de octubre de 2022
Source(s)
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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=080.229.0593.01")
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=080.229.0593.01')
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=080.229.0593.01')