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Description
PINZA PORTA-ALGODON, METALICA, DOS GARRAS EN LAS PUNTAS, LONGITUD 400 A 450 MM.
IMSS product code
537.702.3642.01
Each circle represents one of the 2 purchases of PINZA PARA MATERIAL DIVERSO made by the IMSS between 2014 and 2015.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Tamaulipas Almacen Delegacional En Tamaulipas | Tamaulipas | 1 | 314.2 MXN | 43.3 MXN | 16 % | 0.96 | 28 de agosto de 2014 |
| H. de Traumatología y Ortopedia, "Gral. Div. Manuel Avila Camacho", Centro Médico Nacional, Puebla Umae Traumatologia Y Ortopedia Puebla | Puebla | 1 | 1,392 MXN | 192 MXN | 16 % | 0.16 | 27 de noviembre de 2015 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| MARBELLA ZETINA LAGUNES | 1 | 192 MXN | 16 % | 0.16 | 2015 - 2015 |
| PRECISION QUIRURGICA, S.A. DE C.V. | 1 | 43.3 MXN | 16 % | 0.96 | 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=537.702.3642.01")
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=537.702.3642.01')
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=537.702.3642.01')