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Description
Compra Emergente
IMSS product code
060.345.2152.05
Each circle represents one of the 3 purchases of EQUIPOS made by the IMSS between 2009 and 2009.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Baja California Almacen Delegacional En Baja California Norte | Baja California | 1 | 11,847.7 MXN | - MXN | - | - | 4 de marzo de 2009 |
| Delegación Michoacán Almacen Delegacional En Michoacan | Michoacán | 1 | 84,253.6 MXN | 18,481.2 MXN | 28.1 % | 135.4 | 4 de noviembre de 2009 |
| Delegación Michoacán | Michoacán | 1 | 3,479 MXN | - MXN | - | - | 29 de septiembre de 2009 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| PROMEDICA GARCIA, S. A. DE C. V. | 2 | 18,481.2 MXN | 14 % | 135.4 | 2009 - 2009 |
| SALMED DISTRIBUIDORA, 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=060.345.2152.05")
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=060.345.2152.05')
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=060.345.2152.05')