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Description
TALLA: 25.0. COLOR: BLANCO. CEDULA 46.
Classification
Ropa y Telas. Ropa contractual
IMSS product code
210.005.4051.03
Each circle represents one of the 10 purchases of CALZADO CONTRACTUAL MASCULINO made by the IMSS between 2015 and 2016.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Oficinas Centrales Ofnas Centrales -reforma- Coordinacion De Abastecimiento | 10 | 1.1 millones MXN | 152,933.1 MXN | 16.2 % | 520.3 | 29 de agosto de 2016 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| BECESA, S. A. DE C. V. | 8 | 139,391 MXN | 15.8 % | 473.9 | 2015 - 2016 |
| LINEA EN SEGURIDAD,S. A. DE C. V. | 1 | 7,071.7 MXN | 17.2 % | 22.8 | 2016 - 2016 |
| STRONG EVOLUTION, S.A. DE C.V. | 1 | 6,470.5 MXN | 18.2 % | 23.6 | 2015 - 2015 |
Entity type
Ropa contractual
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=210.005.4051.03")
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=210.005.4051.03')
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=210.005.4051.03')