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Description
CANULAS PARA DRENAR VENAS CAVAS. RECTA CALIBRE 16 FR.
IMSS product code
060.167.3742.11
Each circle represents one of the 11 purchases of CÁNULAS made by the IMSS between 2009 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| H. de Especialidades Cardiológicas No. 34, Centro Médico Nacional del Noreste. Umae Cardiologia En Nuevo Leon | Nuevo León | 11 | 141,455 MXN | 19,388.7 MXN | 15.9 % | 10.3 | 24 de diciembre de 2018 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| EDWARDS LIFESCIENCES MEXICO, S. A. DE C. V. | 4 | 3,123.6 MXN | 9.57 % | 2.26 | 2009 - 2011 |
| SELECCIONES MEDICAS DEL CENTRO. S. A. DE C. V. | 3 | 6,455.7 MXN | 16 % | 2.88 | 2016 - 2018 |
| DIAGNOSTICO Y CIRUGIA, S.A. DE C.V. | 2 | 6,198.4 MXN | 21.6 % | 2.42 | 2012 - 2014 |
| DURFA, S. A. DE C. V. | 1 | 2,555.1 MXN | 29.5 % | 1.77 | 2010 - 2010 |
| TERUMO MEDICAL DE MEXICO, S.A. DE C.V. | 1 | 1,055.9 MXN | 16 % | 0.96 | 2018 - 2018 |
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=060.167.3742.11")
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=060.167.3742.11')
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=060.167.3742.11')