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Description
PINZA, BIPOLAR EN BAYONETA.
IMSS product code
537.702.2909.01
Each circle represents one of the 5 purchases of PINZAS made by the IMSS between 2010 and 2015.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Baja California | Baja California | 2 | 19,691.4 MXN | - MXN | - | - | 10 de febrero de 2010 |
| Delegación Baja California Almacen Delegacional En Baja California Norte | Baja California | 1 | 19,691.4 MXN | 1,951.4 MXN | 11 % | 0.22 | 31 de mayo de 2010 |
| Delegación Hidalgo Almacen Delegacional En Hidalgo | Hidalgo | 1 | 4,640 MXN | 640 MXN | 16 % | 0.16 | 6 de agosto de 2015 |
| Delegación Zacatecas Almacen Delegacional En Zacatecas | Zacatecas | 1 | 8,352 MXN | 1,152 MXN | 16 % | 0.32 | 24 de marzo de 2014 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| RIOS MALDONADO MIGUEL | 3 | 1,951.4 MXN | 3.67 % | 0.22 | 2010 - 2010 |
| QUIRURGICA ORTOPEDICA, S. A. DE C. V. | 2 | 1,792 MXN | 16 % | 0.48 | 2014 - 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=537.702.2909.01")
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=537.702.2909.01')
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=537.702.2909.01')