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Description
SUTURAS, SEDA NEGRA TRENZADA, SIN AGUJA, LONG DE LA HEBRA 75 CM, CAL DE LA SUTURA 1, SOBRE CON 7 A 12 HEBRAS.
IMSS product code
060.841.0775.04
Each circle represents one of the 2 purchases of SUTURAS made by the IMSS between 2009 and 2015.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Chiapas Almacen Subdelegacional En Tuxtla Gutierrez, Chiapas | Chiapas | 1 | 5,003.2 MXN | 690.1 MXN | 16 % | 1.44 | 1 de abril de 2015 |
| H. de Gineco Obstetricia Núm. 23, "Ignacio Morones Prieto" Monterrey, N.L. Umae Gineco - Obstetricia Nuevo Leon | Nuevo León | 1 | 1,313.8 MXN | 171.4 MXN | 15 % | 1.2 | 11 de agosto de 2009 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| FLAVIO AGUILAR VAZQUEZ | 1 | 690.1 MXN | 16 % | 1.44 | 2015 - 2015 |
| SOPORTE MEDICO INTEGRAL, S.A. DE C.V. | 1 | 171.4 MXN | 15 % | 1.2 | 2009 - 2009 |
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=060.841.0775.04")
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=060.841.0775.04')
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=060.841.0775.04')