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Description
CONCENTRADO DE PROTEINAS HUMANAS COAGULABLES. SOLUCION, CADA ML DE SOLUCION RECONSTITUIDA CONTIENE: FIBRINOGENO 70-110 MG, PLASMAFIBRONECTINA 2-9 MG, FACTOR XIII 10-50 UI, PLASMINOGENO 0-120 MICROGRAMOS, APROTININA 3000 UIK,
IMSS product code
010.000.4286.01
Each circle represents one of the 3 purchases of CONCENTRADO DE PROTEÍNAS HUMANAS COAGULABLES made by the IMSS between 2010 and 2010.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| H. de Especialidades No. 1 Centro Médico Nacional del Bajio, León, Gto. Umae Especialidades Guanajuato | Guanajuato | 3 | 67,170 MXN | 6,902.5 MXN | 41.1 % | 1.23 | 23 de diciembre de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| VALLEJO GUANI LAURA CRISTINA | 2 | - MXN | - | - | 2010 - 2010 |
| ISOMEDICA SUPPLY, SA DE CV | 1 | 6,902.5 MXN | 123.3 % | 1.23 | 2010 - 2010 |
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=010.000.4286.01")
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=010.000.4286.01')
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=010.000.4286.01')