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Description
CALCIO EFERVECENTE COMP
IMSS product code
010.000.1006.01
Each circle represents one of the 13 purchases of CALCIO made by the IMSS between 2009 and 2011.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Tamaulipas | Tamaulipas | 9 | 123,246.5 MXN | 16,550.2 MXN | 16.4 % | 96 | 22 de julio de 2011 |
| Delegación Michoacán | Michoacán | 4 | 599.4 MXN | 28.4 MXN | 4.14 % | 0.497 | 26 de noviembre de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| MEMORIAL MEDICA, S.A. DE C.V. | 8 | 16,550.2 MXN | 18.5 % | 96 | 2011 - 2011 |
| Proveedor local no identificado (Compra Emergente) | 4 | 28.4 MXN | 4.14 % | 0.497 | 2009 - 2010 |
| NEOLONESA DE MEDICAMENTOS, S.A. DE C.V. | 1 | - MXN | - | - | 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=010.000.1006.01")
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=010.000.1006.01')
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=010.000.1006.01')