BourdieuVectors library for inferring vectors
Project description
bourdieuvectors is a library that allows to inferr bourdieuvectors. Usage see https://bourdieuvectors.com/.
Installation
Install this library using pip.
Supported Python Versions
Python >= 3.6
Mac/Linux
pip install virtualenv
virtualenv <your-env>
source <your-env>/bin/activate
<your-env>/bin/pip install bourdieuvectors
Windows
pip install virtualenv
virtualenv <your-env>
<your-env>\Scripts\activate
<your-env>\Scripts\pip.exe install bourdieuvectors
Example Usage
Extends a Pandas DataFrame with the vectors.
import pandas as pd
from bourdieuvectors import get_bourdieu_vector
data = pd.DataFrame({
"cultural_event": ["american football"]
})
vector_df = data["cultural_event"].apply(get_bourdieu_vector).apply(pd.Series)
data_with_vectors = pd.concat([data, vector_df], axis=1)
print(data_with_vectors)
data_with_vectors.to_csv("bourdieuvectors_data.csv")
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
bourdieuvectors-0.1.2.tar.gz
(16.8 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file bourdieuvectors-0.1.2.tar.gz.
File metadata
- Download URL: bourdieuvectors-0.1.2.tar.gz
- Upload date:
- Size: 16.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ffe5cd0a6402ae9dfc8b48a4608670ef5b0586c1c25d1fc3aecf165d4445aa5a
|
|
| MD5 |
e621ef746221b7779ee8186d8985cac9
|
|
| BLAKE2b-256 |
8ff7723aa8f358b552f9333671fcc0c05185ff1cfcae5fef08f9c17505a46893
|
File details
Details for the file bourdieuvectors-0.1.2-py2.py3-none-any.whl.
File metadata
- Download URL: bourdieuvectors-0.1.2-py2.py3-none-any.whl
- Upload date:
- Size: 16.5 kB
- Tags: Python 2, Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.1.1 CPython/3.12.12
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
0d3db2ab55caa1eba2e7b4d5e76b5399af3fd3a83dc035f053eeb1a29fe51fe5
|
|
| MD5 |
258a649470cb724b7538e095bd171799
|
|
| BLAKE2b-256 |
bed449a9d5ee7a01c0b895cc37b7a060323d285c74676776cfc54500b06c1bd5
|