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Description
Para drenar venas cavas. Angulada. Calibre: 36 Fr
Classification
Material médico. Material de curacion
IMSS product code
060.166.1820.00
Presentation
Pieza
Each circle represents one of the 5 purchases of CÁNULAS made by the IMSS between 2013 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| H. de Especialidades, "Lic. Ignacio García Tellez" Centro Médico Nacional de Occidente, Jalisco Umae Especialidades Jalisco | Jalisco | 5 | 39,347.2 MXN | 5,427.2 MXN | 15.8 % | 5.12 | 27 de junio de 2018 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| IQ MEDICAL, S. DE R.L. DE C.V. | 3 | 3,071.8 MXN | 16.6 % | 2.13 | 2016 - 2018 |
| INNOVACION CARDIOLOGICA LUMAR, S.A. DE C.V. | 1 | 2,001.9 MXN | 16 % | 2.72 | 2013 - 2013 |
| MEDICAMEX, S. A. DE C. V. | 1 | 353.5 MXN | 13.5 % | 0.27 | 2016 - 2016 |
Entity type
Material de curacion
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=060.166.1820.00")
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=060.166.1820.00')
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=060.166.1820.00')