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Description
Compra Emergente
IMSS product code
060.166.0244.01
Each circle represents one of the 3 purchases of TUBOS made by the IMSS between 2010 and 2010.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Sinaloa | Sinaloa | 2 | 34 MXN | - MXN | - | - | 15 de enero de 2010 |
| H. General, "Dr. Gaudencio González Garza" Centro Médico Nacional La Raza Umae Hospital General C.m.n. La Raza | Ciudad de México | 1 | 2,892.6 MXN | 431.2 MXN | 17.5 % | 14 | 23 de agosto de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| ALVAREZ SALAZAR ELEAZAR | 1 | - MXN | - | - | 2010 - 2010 |
| COMETA MERCANTIL, S.A. DE C.V. | 1 | - MXN | - | - | 2010 - 2010 |
| FRANCISCO GARCIA LOPEZ, S.A. DE C.V. | 1 | 431.2 MXN | 17.5 % | 14 | 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=060.166.0244.01")
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=060.166.0244.01')
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=060.166.0244.01')