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Description
PINZA KAZANJIAN, CORTANTE. LONGITUD TOTAL 200 MM.
IMSS product code
537.702.3386.01
Each circle represents one of the 3 purchases of PINZAS made by the IMSS between 2015 and 2018.
| INSTITUTION | STATE | QUANTITY | TOTAL AMOUNT | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | LAST PURCHASE |
|---|---|---|---|---|---|---|---|
| Delegación Estado de México Poniente Almacen Delegacional En El Estado De Mexico Poniente | Estado de México | 1 | 2,864.8 MXN | 708.1 MXN | 32.8 % | 0.657 | 14 de agosto de 2015 |
| Delegación Hidalgo Almacen Delegacional En Hidalgo | Hidalgo | 1 | 3,389.5 MXN | 154.5 MXN | 4.78 % | 0.143 | 6 de agosto de 2015 |
| Delegación San Luis Potosí Almacen Delegacional En San Luis Potosi | San Luis Potosi | 1 | 5,220 MXN | 720 MXN | 16 % | 0.32 | 24 de julio de 2018 |
| SUPPLIER | PURCHASES | OVERCOST IN MXN | OVERCOST IN % | LOST QUANTITY | TIME PERIOD |
|---|---|---|---|---|---|
| DEWIMED, S. A. | 1 | 708.1 MXN | 32.8 % | 0.657 | 2015 - 2015 |
| NEODREN, S. DE R. L. DE C. V. | 1 | 154.5 MXN | 4.78 % | 0.143 | 2015 - 2015 |
| QUIRURGICA ORTOPEDICA, S. A. DE C. V. | 1 | 720 MXN | 16 % | 0.32 | 2018 - 2018 |
Date updated in QQW
3 de octubre de 2022
Source(s)
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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=537.702.3386.01")
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=537.702.3386.01')
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=537.702.3386.01')