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Description
PLOMO NUMERO 2 SIN GOMA, 7 LONGITUD, 2.2 MM, DIAMETRO
Classification
Artículos de consumo. Utiles de oficina
IMSS product code
312.570.0660.01
Each circle represents one of the 3 purchases of LAPIZ made by the IMSS between 2016 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| H. de Especialidades No. 14 "Adolfo Ruíz Cortines", Veracruz. Umae Especialidades Veracruz (nte.) | Veracruz | 2 | 2,684.6 MXN | 370.3 MXN | 16 % | 289.6 | 28 de febrero de 2018 |
| Delegación Tabasco Almacen Delegacional En Tabasco | Tabasco | 1 | 417.6 MXN | 57.6 MXN | 16 % | 9.6 | 15 de noviembre de 2016 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| DAVLU DISTRIBUIDORA S.A. DE C.V. | 2 | 370.3 MXN | 16 % | 289.6 | 2017 - 2018 |
| GARCIA GOMEZ FILIBERTO | 1 | 57.6 MXN | 16 % | 9.6 | 2016 - 2016 |
Entity type
Utiles de oficina
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=312.570.0660.01")
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=312.570.0660.01')
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=312.570.0660.01')