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Description
JERINGA DE PLASTICO, ESTERILY DESECHABLE, CAPACIDAD 20ML, ESCALA GRADUADA EN MLCON DIVISIONES DE 5.0 Y SUB-DIVISIONES DE 1.0 CON AGUJADE CAL 20 G Y DE LONG 38 MM.
IMSS product code
060.550.0024.10
Each circle represents one of the 4 purchases of JERINGAS made by the IMSS between 2009 and 2015.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Michoacán Almacen Delegacional En Michoacan | Michoacán | 3 | 731,208 MXN | 96,908 MXN | 16.3 % | 5,150 | 18 de mayo de 2010 |
| Delegación Chiapas Almacen Subdelegacional En Tapachula, Chiapas | Chiapas | 1 | 870 MXN | 120 MXN | 16 % | 24 | 13 de octubre de 2015 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| NARVAEZ SANCHEZ LILIANA | 2 | 68,700 MXN | 16.5 % | 4,350 | 2009 - 2009 |
| ARAGON GUTIERREZ ANTONIO | 1 | 28,208 MXN | 16 % | 800 | 2010 - 2010 |
| ENRIQUEZ HERNANDEZ LAURA MARIA | 1 | 120 MXN | 16 % | 24 | 2015 - 2015 |
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=060.550.0024.10")
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=060.550.0024.10')
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=060.550.0024.10')