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Description
GUANTES PARA EXPLORACION, DELATEX, ESTERILES, DESECHA-BLES TAMA\O CHICO (AMBID IES-TRO).
IMSS product code
060.456.0383.10
Each circle represents one of the 2 purchases of GUANTES made by the IMSS between 2009 and 2014.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Chihuahua Almacen Delegacional En Chihuahua | Chihuahua | 1 | 147.6 MXN | 19.2 MXN | 15 % | 0.15 | 23 de abril de 2009 |
| Delegación Veracruz Sur Almacen Delegacional En Veracruz Sur | Veracruz | 1 | 164.4 MXN | 22.7 MXN | 16 % | 0.16 | 27 de noviembre de 2014 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| NUEVO MILENIO DISTRIB. Y MEDICAMENTOS, S.A. DE C.V | 1 | 19.2 MXN | 15 % | 0.15 | 2009 - 2009 |
| QUIRURGICOS E HIPODERMICOS DEL NORESTE, SA DE CV | 1 | 22.7 MXN | 16 % | 0.16 | 2014 - 2014 |
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=060.456.0383.10")
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=060.456.0383.10')
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=060.456.0383.10')