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Description
METENAMINA DISCOS CON 30 - -MCG, EN CARTUCHO CON 50 SENSIDISCOS PARA DISTRIBUIDORAUTOMATICO RTC.
IMSS product code
080.316.3930.04
Each circle represents one of the 5 purchases of DISCOS CON ANTIMICROBIANOS made by the IMSS between 2010 and 2013.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Chihuahua | Chihuahua | 2 | 7,516.8 MXN | 0.000000000000909 MXN | 0.0000000000000121 % | 0.000000000000000842 | 31 de enero de 2013 |
| Delegación Chiapas Almacen Subdelegacional En Tapachula, Chiapas | Chiapas | 1 | 472.9 MXN | 311.9 MXN | 193.7 % | 5.81 | 3 de marzo de 2011 |
| Delegación Chihuahua Almacen Delegacional En Chihuahua | Chihuahua | 1 | 13,885.2 MXN | 1,650.2 MXN | 13.5 % | 30.8 | 4 de marzo de 2011 |
| Delegación Michoacán Almacen Delegacional En Michoacan | Michoacán | 1 | 83,520 MXN | 11,520 MXN | 16 % | 9.6 | 24 de febrero de 2010 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| RODRIGUEZ MENDOZA SALVADOR FERNANDO | 2 | 0.000000000000909 MXN | 0.0000000000000121 % | 0.000000000000000842 | 2012 - 2013 |
| COMERCIALIZADORA MYL PRODUCTOS, S.A. DE C.V. | 1 | 311.9 MXN | 193.7 % | 5.81 | 2011 - 2011 |
| RAMIREZ ROMERO JESUS ARMANDO | 1 | 1,650.2 MXN | 13.5 % | 30.8 | 2011 - 2011 |
| ZAVALA ACU?A CRISTY PAULINA | 1 | 11,520 MXN | 16 % | 9.6 | 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=080.316.3930.04")
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=080.316.3930.04')
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=080.316.3930.04')