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Documentation Index

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Every notebook in this project reads its configuration from two sources: a .env file for secrets (API credentials), and a set of pathlib.Path constants defined at the top of each notebook for filesystem navigation. Understanding these two layers makes it straightforward to adapt the project to a different machine, a shared server, or a different working directory.

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Environment file (.env)

The project uses python-dotenv to load secrets from a .env file in the project root. The repository ships with .env.example as a committed template — copy it to .env and fill in your real values before running notebook 01. 
cp .env.example .env
Notebooks 02, 03, 04, and 05 do not read any environment variables. They work entirely with pre-existing CSV files in data/clean/ and data/raw/. Only notebook 01 (01_data_collection.ipynb) requires Adzuna credentials to be present in .env.

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Variables

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ADZUNA_APP_ID
string
required
Your Adzuna application ID. Obtain this by registering a free developer account at developer.adzuna.com. Used exclusively by notebook 01 to authenticate paginated API requests.
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ADZUNA_APP_KEY
string
required
Your Adzuna application key (API secret). Retrieved from the same developer dashboard as ADZUNA_APP_ID. Sent as a query parameter on every Adzuna API call.

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.env.example template

The committed example file shows the expected format: 
# Adzuna API credentials
# Rename this file to .env and fill with your real keys
ADZUNA_APP_ID=d909c217
ADZUNA_APP_KEY=986a17c866ebfa14a61cf578aebf0a30
The values shown in .env.example are placeholder keys. Never use them in production requests. Always replace them with the keys from your own Adzuna developer account.

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Loading variables in notebook 01

Notebook 01 loads the .env file using the standard python-dotenv pattern: 
from dotenv import load_dotenv
import os

load_dotenv()

APP_ID  = os.getenv('ADZUNA_APP_ID')
APP_KEY = os.getenv('ADZUNA_APP_KEY')
load_dotenv() reads the .env file from the current working directory (or any parent directory) and injects each key-value pair into os.environ. The variables are then available via os.getenv() for the remainder of the kernel session.
If load_dotenv() returns False, the .env file was not found. Make sure you have copied .env.example to .env and that the file lives in the project root — not inside the notebooks/ subdirectory.

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Path constants

All five notebooks define the same set of pathlib.Path constants in their first cell. This pattern resolves the project root regardless of whether the notebook is opened from within the notebooks/ subdirectory or from the project root directly. 
from pathlib import Path

PROJECT_ROOT = Path.cwd().parent if Path.cwd().name == "notebooks" else Path.cwd()
DATA_RAW     = PROJECT_ROOT / "data" / "raw"
DATA_CLEAN   = PROJECT_ROOT / "data" / "clean"

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How the root resolution works

ConditionPath.cwd()PROJECT_ROOT resolves to
Notebook opened from notebooks/.../proyecto-eda-roles-datos/notebooks.../proyecto-eda-roles-datos
Notebook opened from project root.../proyecto-eda-roles-datos.../proyecto-eda-roles-datos
This makes all downstream paths stable:
ConstantResolved path
PROJECT_ROOTproyecto-eda-roles-datos/
DATA_RAWproyecto-eda-roles-datos/data/raw/
DATA_CLEANproyecto-eda-roles-datos/data/clean/

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Extended path constants

Some notebooks define additional constants for EDA outputs and images: 
DATA_EDA = PROJECT_ROOT / "data" / "eda"
IMAGES   = PROJECT_ROOT / "images"
These directories are created automatically by the notebooks if they do not exist. No manual mkdir is required.

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Notebook-level configuration

Beyond environment variables and paths, each notebook sets a few display and styling options in its setup cell. These are not stored in .env — they are hardcoded constants at the top of each notebook.

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pandas display options

import pandas as pd

pd.set_option("display.max_columns", None)   # Show all columns
pd.set_option("display.max_rows", 100)        # Cap row output in notebooks
pd.set_option("display.float_format", "{:.2f}".format)  # 2 decimal places
pd.set_option("display.width", 120)           # Wider console output

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seaborn theme

import seaborn as sns

sns.set_theme(style="whitegrid", palette="muted")
Notebook 04 overrides the seaborn palette locally per chart to match the project’s colour scheme (blues and oranges). The global set_theme call in the setup cell only provides a baseline default.

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matplotlib defaults

import matplotlib.pyplot as plt
import matplotlib.ticker as mticker

plt.rcParams["figure.figsize"] = (12, 6)
plt.rcParams["figure.dpi"]     = 150
plt.rcParams["font.family"]    = "sans-serif"

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Plotly renderer

import plotly.io as pio

pio.renderers.default = "jupyterlab"  # Interactive display in Jupyter Lab
For static PNG export (used in notebook 04), kaleido is called explicitly via fig.write_image() — no additional renderer configuration is needed.

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Security checklist

.env is gitignored

Confirm .gitignore includes .env before pushing to a public repository. The file is excluded by default, but verify after any .gitignore edits.

No hardcoded secrets

API credentials must never appear in notebook cells or script files. Always load them via os.getenv() after calling load_dotenv().

Use separate keys per environment

If you deploy this project on a shared server or CI pipeline, create a separate Adzuna API key for that environment and rotate keys regularly.

Rotate compromised keys immediately

If a key is accidentally committed, revoke it immediately in the Adzuna developer dashboard and generate a new one.

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