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Description
TIJERAS, ANGULADAS HACIA ARRIBA. LONGITUD DE TRABAJO 100 MM.
IMSS product code
537.857.1391.01
Each circle represents one of the 2 purchases of TIJERA made by the IMSS between 2010 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Querétaro Almacen Delegacional En Queretaro | Querétaro | 1 | 2,596.2 MXN | 358.1 MXN | 16 % | 0.32 | 31 de julio de 2018 |
| Delegación Tamaulipas Almacen Delegacional En Tamaulipas | Tamaulipas | 1 | 730.8 MXN | 100.8 MXN | 16 % | 0.96 | 7 de julio de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| COMERCIALIZADORA INTEGRAL Y DE SERV. MIRSO, S. A. | 1 | 100.8 MXN | 16 % | 0.96 | 2010 - 2010 |
| DEWIMED, S. A. | 1 | 358.1 MXN | 16 % | 0.32 | 2018 - 2018 |
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=537.857.1391.01")
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=537.857.1391.01')
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=537.857.1391.01')