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Description
Compra Emergente
IMSS product code
060.725.0594.12
Each circle represents one of the 3 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 Chihuahua | Chihuahua | 1 | 1,640.3 MXN | 0.00494 MXN | 0.000301 % | 0.00000347 | 29 de enero de 2009 |
| Delegación Sinaloa | Sinaloa | 1 | 2,126.3 MXN | - MXN | - | - | 6 de enero de 2011 |
| Delegación Sonora Almacen Delegacional En Sonora | Sonora | 1 | 4,050.7 MXN | 1,388.2 MXN | 52.1 % | 0.521 | 29 de abril de 2011 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| HEMOST, S. A. DE C. V. | 2 | 0.00494 MXN | 0.000151 % | 0.00000347 | 2009 - 2011 |
| MARA IRASEMA CASTRO ACU?A | 1 | 1,388.2 MXN | 52.1 % | 0.521 | 2011 - 2011 |
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=060.725.0594.12")
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=060.725.0594.12')
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=060.725.0594.12')