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Description
Compra Emergente
IMSS product code
060.189.0049.01
Each circle represents one of the 4 purchases of CEPILLOS 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 | Baja California | 3 | 2,800.6 MXN | 1,978.3 MXN | 1,471 % | 215.2 | 30 de noviembre de 2009 |
| Delegación Jalisco | Jalisco | 1 | 330.6 MXN | - MXN | - | - | 30 de noviembre de 2009 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| INSTRUMENTACION Y EQUIPOS MEDICOS, S. DE R.L. DE C | 2 | 378.9 MXN | 624.5 % | 41.2 | 2009 - 2009 |
| DIAGNOSTICA COMERCIAL, S.A. DE C.V. | 1 | 1,599.4 MXN | 3,163.9 % | 174 | 2009 - 2009 |
| ELECTRO PAPER, 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=060.189.0049.01")
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=060.189.0049.01')
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=060.189.0049.01')