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Description
Compra Emergente
IMSS product code
060.167.7966.12
Each circle represents one of the 3 purchases of CATÉTERES made by the IMSS between 2010 and 2015.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Estado de México Poniente Almacen Delegacional En El Estado De Mexico Poniente | Estado de México | 2 | 531,703.1 MXN | 73,338.4 MXN | 16 % | 36.2 | 23 de febrero de 2015 |
| Delegación Estado de México Poniente | Estado de México | 1 | 972.2 MXN | 0.00403 MXN | 0.000414 % | 0.00000481 | 10 de febrero de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| COMERCIALIZADORA GLAVS, S.A. DE C.V. | 1 | 70,656 MXN | 16 % | 30.7 | 2015 - 2015 |
| NORMA BASURTO RODRIGUEZ | 1 | 2,682.4 MXN | 16 % | 5.44 | 2011 - 2011 |
| Proveedor local no identificado (Compra Emergente) | 1 | 0.00403 MXN | 0.000414 % | 0.00000481 | 2010 - 2010 |
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=060.167.7966.12")
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=060.167.7966.12')
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=060.167.7966.12')