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Description
GLUCOSA 10 MG/ML. RTC. FRASCO CON 100 ML.
IMSS product code
080.823.1278.11
Each circle represents one of the 2 purchases of CONTROLES Y ESTÁNDARES made by the IMSS between 2012 and 2012.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Baja California | Baja California | 1 | 666 MXN | - MXN | - | - | 14 de febrero de 2012 |
| Delegación Chihuahua Almacen Delegacional En Chihuahua | Chihuahua | 1 | 18,875.5 MXN | 4,912.5 MXN | 35.2 % | 16.9 | 16 de febrero de 2012 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| CLINIBAC, S DE R.L. DE C.V. | 1 | - MXN | - | - | 2012 - 2012 |
| CONTROL TECNICO Y REPRESENTACIONES, S. A. DE C. V. | 1 | 4,912.5 MXN | 35.2 % | 16.9 | 2012 - 2012 |
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=080.823.1278.11")
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=080.823.1278.11')
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=080.823.1278.11')