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Description
Compra Emergente
IMSS product code
080.909.1341.01
Each circle represents one of the 3 purchases of TUBOS made by the IMSS between 2009 and 2010.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Aguascalientes | Aguascalientes | 1 | 862.5 MXN | - MXN | - | - | 24 de julio de 2009 |
| Delegación Baja California | Baja California | 1 | 2,387 MXN | 1,864.2 MXN | 356.6 % | 3.57 | 10 de diciembre de 2009 |
| Delegación Tamaulipas | Tamaulipas | 1 | 1,113.6 MXN | - MXN | - | - | 11 de agosto de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| COMERCIAL ALPRO, S.A. DE C.V. | 1 | - MXN | - | - | 2010 - 2010 |
| DISTRIBUIDORA QUIRURGICA NACIONAL, S. A. DE C. V. | 1 | - MXN | - | - | 2009 - 2009 |
| GONZALEZ FLORES CARLOS ALBERTO | 1 | 1,864.2 MXN | 356.6 % | 3.57 | 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=080.909.1341.01")
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=080.909.1341.01')
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=080.909.1341.01')