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Description
Compra Emergente
IMSS product code
060.899.0818.10
Each circle represents one of the 4 purchases of PLACAS made by the IMSS between 2009 and 2011.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Tabasco | Tabasco | 2 | 1,658.8 MXN | - MXN | - | - | 20 de enero de 2011 |
| Delegación Coahuila | Coahuila | 1 | 1,725 MXN | 1,104 MXN | 177.8 % | 2.04 | 12 de mayo de 2009 |
| Delegación Guanajuato | Guanajuato | 1 | 138 MXN | - MXN | - | - | 26 de marzo de 2009 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| FERNANDEZ DE LARA CASTILLO JUAN MANUEL | 2 | - MXN | - | - | 2010 - 2011 |
| MEDIPAR, S.A. DE C.V. | 1 | 1,104 MXN | 177.8 % | 2.04 | 2009 - 2009 |
| QUIRURGICA ORTOPEDICA, S.A. DE C.V. | 1 | - MXN | - | - | 2009 - 2009 |
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=060.899.0818.10")
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=060.899.0818.10')
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=060.899.0818.10')