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Description
GOMA DE KARAYA. EN POLVO.
IMSS product code
060.440.0010.11
Each circle represents one of the 34 purchases of GOMA made by the IMSS between 2009 and 2017.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| H. Traumatología "Dr. Victorio De La Fuente Narváez" Umae Trauma Y Orto M.s. "dr. Victorio De La Fuente Narvaez" (d.f. Nort | Ciudad de México | 12 | 30,873.4 MXN | 6,879.7 MXN | 29 % | 11.3 | 22 de septiembre de 2015 |
| H. General, "Dr. Gaudencio González Garza" Centro Médico Nacional La Raza Umae Hospital General C.m.n. La Raza | Ciudad de México | 9 | 155,426.7 MXN | 27,169.1 MXN | 18.9 % | 35.7 | 23 de marzo de 2017 |
| H. de Especialidades, "Dr. Bernardo Sepulveda Gutiérrez" Centro Médico Nacional Siglo XXI Umae Especialidades C.m.n. Siglo Xxi | Ciudad de México | 7 | 722,752 MXN | 94,556.3 MXN | 15.1 % | 167.4 | 12 de septiembre de 2012 |
| Delegación Durango Almacen Delegacional En Durango | Durango | 3 | 12,756.3 MXN | 919.6 MXN | 12.6 % | 1.4 | 8 de enero de 2014 |
| Delegación Querétaro Almacen Delegacional En Queretaro | Querétaro | 2 | 9,418.3 MXN | 1,030.4 MXN | 43.5 % | 1.74 | 30 de junio de 2015 |
| Delegación Quintana Roo Almacen Delegacional En Quintana Roo | Quintana Roo | 1 | 15,677.3 MXN | 36.7 MXN | 0.235 % | 0.0563 | 6 de junio de 2017 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| FARMACIAS DE ESPECIALIDADES DERMATOLOGICAS DE MEXI | 7 | 94,556.3 MXN | 15.1 % | 167.4 | 2009 - 2012 |
| GARRIDO LEDESMA GABRIEL ANGEL | 5 | 3,003.4 MXN | 37 % | 5.01 | 2012 - 2013 |
| Q.M.H. ABASTECEDORES, S. A. DE C. V. | 5 | 3,117.6 MXN | 25.6 % | 5.37 | 2009 - 2011 |
| DIBICO, S. A. DE C. V. | 2 | 11,646.4 MXN | 13 % | 12.8 | 2014 - 2015 |
| DOMINGUEZ ARANGO NALLELY IVONNE | 2 | 7,158.2 MXN | 13.7 % | 11 | 2014 - 2017 |
| ESCAMILLA ZENTENO AURORA | 2 | 229.2 MXN | 5.15 % | 0.412 | 2010 - 2011 |
| JTC PROVEEDOR MEDICO, S. A. DE C. V. | 2 | 374.2 MXN | 16.3 % | 0.651 | 2010 - 2011 |
| ALGE DEL BAJIO, S.A. DE C.V. | 1 | 1,030.4 MXN | 87 % | 1.74 | 2012 - 2012 |
| APARATOS BIOTECNOLOG. Y CONS. DE MEX., SA DE CV | 1 | 1,484.2 MXN | 50.3 % | 2.51 | 2011 - 2011 |
| CASLAB DE MEXICO, S. A. DE C. V. | 1 | 36.7 MXN | 0.235 % | 0.0563 | 2017 - 2017 |
| COMERCIALIZADORA LINI, S.A. DE C.V. | 1 | 196.9 MXN | 21.5 % | 0.215 | 2015 - 2015 |
| COMERCIALIZADORA PARA HOSP. GALA, S.A. DE C.V. | 1 | 577.8 MXN | 12.7 % | 0.764 | 2014 - 2014 |
| EMPRESAS ERI, S. A. DE C. V. | 1 | 5,806.7 MXN | 21.9 % | 7.68 | 2014 - 2014 |
| INSUMOS Y SOLUCIONES MEDICAS, SA DE CV | 1 | 635.1 MXN | 21.5 % | 1.07 | 2012 - 2012 |
| MARTHA ANDREA BARRERA MCDONALD | 1 | - MXN | - | - | 2015 - 2015 |
| PROVEEDORA MEX. DE ARTS. DE CUR. Y LAB, SA CV | 1 | 738.4 MXN | 18.9 % | 0.943 | 2013 - 2013 |
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=060.440.0010.11")
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=060.440.0010.11')
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=060.440.0010.11')