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Description
PARA IMPRESORA MARCA OKI MODELOS ES5112 Y ES5162, NUMERO DE PARTE 45807115
Classification
Material médico. Material de uso en equipos de computo
IMSS product code
372.197.5955.00
Each circle represents one of the 43 purchases of CARTUCHO DE TONER made by the IMSS between 2016 and 2019.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Coahuila Almacen Delegacional En Coahuila | Coahuila | 4 | 31 millones MXN | 8.3 millones MXN | 38.8 % | 2,750.6 | 26 de julio de 2018 |
| Delegación Guanajuato Almacen Delegacional En Guanajuato | Guanajuato | 4 | 6 millones MXN | 1.8 millones MXN | 51.4 % | 660.8 | 22 de enero de 2018 |
| Delegación Norte del DF Almacen Delegacional En El D.f. Zona Norte | Ciudad de México | 4 | 98.7 millones MXN | 9.7 millones MXN | 8.9 % | 3,293.4 | 1 de enero de 2019 |
| H. Traumatología "Dr. Victorio De La Fuente Narváez" Umae Trauma Y Orto M.s. "dr. Victorio De La Fuente Narvaez" (d.f. Nort | Ciudad de México | 4 | 1.2 millones MXN | 149,608.1 MXN | 72.8 % | 48.6 | 19 de julio de 2018 |
| Delegación Estado de México Oriente Almacen Delegacional En Estado De Mexico Oriente | Estado de México | 3 | 76.1 millones MXN | 2.5 millones MXN | 3.03 % | 926.1 | 15 de junio de 2017 |
| Delegación Michoacán Almacen Delegacional En Michoacan | Michoacán | 3 | 6 millones MXN | 1.6 millones MXN | 33.9 % | 580.2 | 10 de febrero de 2017 |
| Delegación Puebla Almacen Delegacional En Puebla | Puebla | 3 | 14.4 millones MXN | 616,349.3 MXN | 6.24 % | 200.1 | 24 de agosto de 2018 |
| H. de Especialidades, "Lic. Ignacio García Tellez" Centro Médico Nacional de Occidente, Jalisco Umae Especialidades Jalisco | Jalisco | 3 | 2.7 millones MXN | 851,180.2 MXN | 45.5 % | 308.4 | 13 de noviembre de 2017 |
| H. de Oncología, Centro Médico Nacional Siglo XXI Umae Oncologia C.m.n. Siglo Xxi | Ciudad de México | 3 | 259,028 MXN | 14,514.4 MXN | 3.34 % | 5.01 | 23 de abril de 2018 |
| Delegación Jalisco Almacen Delegacional En Jalisco | Jalisco | 2 | 27.3 millones MXN | 8.5 millones MXN | 45.2 % | 3,135 | 9 de enero de 2017 |
| Delegación Yucatán Almacen Delegacional En Yucatan | Yucatán | 2 | 9.7 millones MXN | 3.3 millones MXN | 52.1 % | 1,185.9 | 5 de enero de 2017 |
| H. de Cardiología, Centro Médico Nacional Siglo XXI Umae Cardiologia C.m.n. Siglo Xxi | Ciudad de México | 2 | 607,840 MXN | 80,145.2 MXN | 15.5 % | 26.9 | 9 de marzo de 2018 |
| H. de Especialidades, "Dr. Antonio Fraga Mouret" Centro Médico Nacional La Raza Umae Especialidades C.m.n. La Raza | Ciudad de México | 2 | 76,339.6 MXN | 11,461.8 MXN | 16.2 % | 3.9 | 26 de marzo de 2018 |
| Delegación Querétaro Almacen Delegacional En Queretaro | Querétaro | 1 | 3.7 millones MXN | 971,759.6 MXN | 35.6 % | 335.1 | 16 de enero de 2017 |
| Delegación Sur del DF Almacen Delegacional En El D.f. Zona Sur | Ciudad de México | 1 | 10.8 millones MXN | 1.4 millones MXN | 15.3 % | 546.5 | 19 de febrero de 2016 |
| H. de Especialidades Núm 71, Torreón, Coahuila Umae Especialidades Coahuila | Coahuila | 1 | 416,556 MXN | 30,894.3 MXN | 8.01 % | 10.7 | 1 de enero de 2017 |
| H. de Gineco Obstetricia No. 3 "Dr. Víctor Manuel Espinosa de los Reyes Sánchez" La Raza Umae Gineco - Obstetricia La Raza | Ciudad de México | 1 | 206,712 MXN | 15,331 MXN | 8.01 % | 5.29 | 31 de marzo de 2017 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| SOURCE TONER DE MEXICO, S.A. DE C.V. | 10 | 9.3 millones MXN | 6.28 % | 3,238.1 | 2016 - 2018 |
| ACCECOMPU, S.A. DE C.V. | 5 | 8.3 millones MXN | 32.7 % | 2,761.3 | 2017 - 2018 |
| VALMAR DIGITALMICRO, S.A. DE C.V. | 5 | 9.4 millones MXN | 45.4 % | 3,443.4 | 2016 - 2017 |
| GRUPO PALIBA S.A. DE C.V. | 4 | 1.8 millones MXN | 51.4 % | 660.8 | 2016 - 2018 |
| LIRA Y HERNANDEZ, S. A. DE C. V. | 4 | 109,990.6 MXN | 12.3 % | 37.2 | 2016 - 2018 |
| OFIVILLANELY, S DE R.L. DE C.V. | 3 | 1.6 millones MXN | 33.9 % | 580.2 | 2016 - 2017 |
| SALCEDO BOTELLO OSCAR MANUEL | 3 | 132,923.3 MXN | 6.81 % | 43.2 | 2018 - 2018 |
| CIBERTONER, S. DE R.L. DE C.V. | 2 | 3.3 millones MXN | 52.1 % | 1,185.9 | 2016 - 2017 |
| COMERCIALIZADORA EFEXCA, S.A. DE C.V. | 2 | 11,461.8 MXN | 16.2 % | 3.9 | 2017 - 2018 |
| COMERCIALIZADORA TONYCOM,S.A DE C.V | 1 | - MXN | - | - | 2018 - 2018 |
| GRUPO CONSU-OFFICE S. DE R.L. DE C.V. | 1 | - MXN | - | - | 2018 - 2018 |
| LEAMSI, S.A. DE C.V. | 1 | 16,684.8 MXN | 270.8 % | 5.42 | 2018 - 2018 |
| TCA EMPRESARIAL, S.A. DE C.V. | 1 | 971,759.6 MXN | 35.6 % | 335.1 | 2017 - 2017 |
| VETEF, S.A. DE C.V. | 1 | 5 millones MXN | 16 % | 1,728 | 2019 - 2019 |
Entity type
Material de uso en equipos de computo
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=372.197.5955.00")
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=372.197.5955.00')
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=372.197.5955.00')