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Description
PINZA BERKE, QUIJADA CORTA. LONGITUD DE 100 MM.
IMSS product code
537.704.0232.01
Each circle represents one of the 2 purchases of PINZA DE SUJECIÓN TRACCIÓN FIJACIÓN made by the IMSS between 2016 and 2017.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Chiapas Almacen Subdelegacional En Tapachula, Chiapas | Chiapas | 1 | 1,114.3 MXN | 153.7 MXN | 16 % | 0.16 | 21 de abril de 2017 |
| Delegación Chiapas Almacen Subdelegacional En Tuxtla Gutierrez, Chiapas | Chiapas | 1 | 1,114.3 MXN | 153.7 MXN | 16 % | 0.16 | 20 de julio de 2016 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| SUMINISTROS MEDICOS AVANZADOS S.A. DE C.V | 1 | 153.7 MXN | 16 % | 0.16 | 2016 - 2016 |
| SUPPORT GLOBAL BIOMEDICAL GROUP, S.A. DE C.V. | 1 | 153.7 MXN | 16 % | 0.16 | 2017 - 2017 |
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=537.704.0232.01")
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=537.704.0232.01')
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=537.704.0232.01')