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Description
Compra Emergente
IMSS product code
080.431.0043.10
Each circle represents one of the 4 purchases of FRASCOS made by the IMSS between 2009 and 2014.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Morelos | Morelos | 3 | 11,971.5 MXN | 11,518.6 MXN | 6,488.7 % | 224.6 | 6 de junio de 2009 |
| Delegación Querétaro Almacen Delegacional En Queretaro | Querétaro | 1 | 3,596 MXN | 496 MXN | 16 % | 80 | 28 de noviembre de 2014 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| LEON GARCIA MARCO ANTONIO | 2 | 77.6 MXN | 32.9 % | 1.51 | 2009 - 2009 |
| BIOTECNOLOGIA Y SERVICIOS, S.A. DE C.V. | 1 | 11,441 MXN | 19,400.5 % | 223.1 | 2009 - 2009 |
| MARIA ISABEL MONTA?O GUTIERREZ | 1 | 496 MXN | 16 % | 80 | 2014 - 2014 |
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=080.431.0043.10")
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=080.431.0043.10')
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=080.431.0043.10')