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https://github.com/jaimemosg/census_api_challenge
This is just my first fastAPI
https://github.com/jaimemosg/census_api_challenge
fastapi jupyter-notebook
Last synced: about 2 months ago
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This is just my first fastAPI
- Host: GitHub
- URL: https://github.com/jaimemosg/census_api_challenge
- Owner: Jaimemosg
- Created: 2021-04-14T15:04:16.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2021-04-16T00:02:59.000Z (almost 4 years ago)
- Last Synced: 2024-11-09T22:24:19.607Z (3 months ago)
- Topics: fastapi, jupyter-notebook
- Language: Jupyter Notebook
- Homepage:
- Size: 25.3 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Challenge: API for census-income data base
This API returns filters the `census-income + (KDD)` data set and computes the mean, minumum and maximum wage per hour, the minumum and maximum weeks worked by an employee, the number of employees whose income is greater than 50k and the total number of employees filtered.
## Info
In this repo you can find:
- `documentation/census_BD.pdf`: the entity-raletion diagram.
- `EDA_census.ipnb`: Jupyter notebook cwith EDA (Exploratory Data Analysis and Analytics).
- `RDB_creation.ipynb`: Jupyter notebook for data base creation.
## Remote
This API was deployed at Heroku where you can also test it from the docs endpoint
[https://fastapi-census.herokuapp.com/docs](https://fastapi-census.herokuapp.com/docs)
## Local use
### 1. Install requirements
```
pip install -r requirements.txt --no-cache-dir
```
### 2. Change to app folder
```
cd census_api_challenge
```
### 3. Run de app
* Use --reload only in dev environment
```
uvicorn app:app --reload --port 8000
```
### 4. Go to localhost
http://127.0.0.1:8000/docs
### 5. Stop the server
```
ctrl + c
```
## Usage (example)
### Example 1
You could perform a query such the following
```
{
"age": 31,
"class_of_worker": "Private",
"industry_code": 43,
"occupation_code": 7,
"marital_status": "Never married",
"major_industry_code": "Education",
"major_occupation_code": "Professional specialty",
"hispanic_origin": "Mexican (Mexicano)",
"sex": "Female"
}
```
You should obtain the following response:
```
[
{
"mean_wage": 0,
"mean_weeks_worked": 46.666666666666664,
"min_wage": 0,
"min_weeks_worked": 12,
"max_wage": 0,
"max_weeks_worked": 52,
"person_50k_plus": 4,
"num_person": 12
}
]
```
### Example 2
Another possible query is the following
```
{
"age": 43,
"class_of_worker": "Private",
"industry_code": 43,
"occupation_code": 7
}
```
What was the answer?
---
By **Jaime Mosquera Gútiérrez** - [Jaimemosg](https://github.com/Jaimemosg)