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Description
MEDIOS DE CONTRASTE. GRUPO13: MATERIALES PARA ESTUDIOSDE RADIOLOGIA E IMAGEN. GRA-NULADO EFERVESCENTE CON: BI-CARBONATO DE SODIO 0.460 GACIDO TARTARICO 0.420 G SIMETICONA C.B.P. 1 G.
IMSS product code
070.591.0016.10
Each circle represents one of the 4 purchases of MEDIOS DE CONTRASTE made by the IMSS between 2009 and 2014.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Aguascalientes Almacen Delegacional En Aguascalientes | Aguascalientes | 1 | 1,470.2 MXN | 191.8 MXN | 15 % | 6 | 17 de abril de 2009 |
| Delegación Estado de México Poniente Almacen Delegacional En El Estado De Mexico Poniente | Estado de México | 1 | 6,496 MXN | 896 MXN | 16 % | 32 | 15 de agosto de 2012 |
| Delegación Michoacán Almacen Delegacional En Michoacan | Michoacán | 1 | 42,705.4 MXN | 5,890.4 MXN | 16 % | 29.6 | 27 de octubre de 2010 |
| Delegación Norte del DF Almacen Delegacional En El D.f. Zona Norte | Ciudad de México | 1 | 24,360 MXN | 3,360 MXN | 16 % | 120 | 6 de agosto de 2014 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| JUAMA, S.A. DE C.V. | 2 | 4,256 MXN | 16 % | 152 | 2012 - 2014 |
| DISTRIBUIDORA GOBA DE QUERETARO, S.A DE C.V | 1 | 191.8 MXN | 15 % | 6 | 2009 - 2009 |
| GRUPO LAMPORT, S. DE R.L. DE C.V. | 1 | 5,890.4 MXN | 16 % | 29.6 | 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=070.591.0016.10")
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=070.591.0016.10')
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=070.591.0016.10')