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Classification
Material médico. Material de curacion
IMSS product code
060.899.2202.10
Each circle represents one of the 11 purchases of COMPRA EMERGENTE made by the IMSS between 2009 and 2010.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Guanajuato | Guanajuato | 9 | 1,555.3 MXN | - MXN | - | - | 3 de abril de 2009 |
| Delegación Chiapas | Chiapas | 1 | 1,915.9 MXN | 1,846.5 MXN | 2,659.7 % | 30.6 | 25 de mayo de 2009 |
| Delegación Sinaloa | Sinaloa | 1 | 233.5 MXN | - MXN | - | - | 17 de marzo de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| QUIRURGICA ORTOPEDICA, S. A. DE C. V. | 10 | - MXN | - | - | 2009 - 2010 |
| PE?A HERNANDEZ MARIA DE JESUS | 1 | 1,846.5 MXN | 2,659.7 % | 30.6 | 2009 - 2009 |
Entity type
Material de curacion
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=060.899.2202.10")
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=060.899.2202.10')
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=060.899.2202.10')