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Description
Compra Emergente
IMSS product code
060.168.6686.01
Each circle represents one of the 12 purchases of CATÉTERES made by the IMSS between 2009 and 2011.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Guerrero | Guerrero | 8 | 8,901 MXN | 5,462.3 MXN | 168.4 % | 38.6 | 4 de junio de 2009 |
| Delegación Sonora Almacen Delegacional En Sonora | Sonora | 4 | 3,139.5 MXN | 901.3 MXN | 40 % | 5.43 | 7 de noviembre de 2011 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| VALLE CASTILLO ABEL | 5 | 4,254.9 MXN | 217.6 % | 30 | 2009 - 2009 |
| DINORSA, S.A. DE C.V. | 3 | 267.5 MXN | 16 % | 0.96 | 2011 - 2011 |
| DE LEON TRINIDAD MARIA JANET | 2 | 1,207.4 MXN | 129.4 % | 8.52 | 2009 - 2009 |
| COMERCIALIZADORA Y DISTRIBUIDORA ECAS | 1 | 633.9 MXN | 111.9 % | 4.47 | 2009 - 2009 |
| LARA GARCIA ADRIANA | 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=060.168.6686.01")
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=060.168.6686.01')
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=060.168.6686.01')