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Description
LECTINA ANTI H (FITOAGLUTININA) FRASCO DE 2 ML RTC.
IMSS product code
080.081.0244.01
Each circle represents one of the 2 purchases of SUSTANCIAS BIOLOGICAS made by the IMSS between 2010 and 2010.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Estado de México Oriente Almacen Delegacional En Estado De Mexico Oriente | Estado de México | 1 | 322.5 MXN | - MXN | - | - | 27 de enero de 2010 |
| H. de Gineco Obstetricia No. 3 "Dr. Víctor Manuel Espinosa de los Reyes Sánchez" La Raza Umae Gineco - Obstetricia La Raza | Ciudad de México | 1 | 11,275.2 MXN | 1,677.1 MXN | 17.5 % | 4.19 | 10 de febrero de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| INSTRUMENTOS Y EQUIPOS FALCON, S. A. DE C. V. | 1 | 1,677.1 MXN | 17.5 % | 4.19 | 2010 - 2010 |
| QUIMICA INDUSTRIAL Y DE SALUD, SA DE CV | 1 | - MXN | - | - | 2010 - 2010 |
Date updated in QQW
3 de octubre de 2022
Source(s)
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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=080.081.0244.01")
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=080.081.0244.01')
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=080.081.0244.01')