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Description
PINZA FERRIS-KERRISON-SMITH, CORTE HACIA ARRIBA, PUNTA ANGULADA A 130 GRADOS MORDIDA DE 2 MM. LONGITUD TOTAL 180 MM.
IMSS product code
537.702.3238.01
Each circle represents one of the 14 purchases of PINZAS made by the IMSS between 2009 and 2018.
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| MARBELLA ZETINA LAGUNES | 5 | 19,806.3 MXN | 21 % | 3.06 | 2011 - 2015 |
| QUIRURGICA ORTOPEDICA, S. A. DE C. V. | 3 | 4,425.8 MXN | 16 % | 1.12 | 2017 - 2018 |
| HIDRO HOSPITAL, S.A. DE C.V. | 2 | 459.7 MXN | 2.47 % | 0.0987 | 2010 - 2010 |
| DEWIMED, S. A. | 1 | 1,197.9 MXN | 15 % | 0.15 | 2009 - 2009 |
| FERNANDO MIGUEL SALAZAR DEL VALLE | 1 | 5,593.8 MXN | 60.1 % | 1.2 | 2010 - 2010 |
| IMPORTADORA MEDICA MEXICANA, S. A. | 1 | 10,543.6 MXN | 63.8 % | 1.28 | 2012 - 2012 |
| NEODREN, S. DE R. L. DE C. V. | 1 | - MXN | - | - | 2015 - 2015 |
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=537.702.3238.01")
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=537.702.3238.01')
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=537.702.3238.01')