Package Documentation

This page describes the main functions available in the national_parks package.

get_parks_data()

Description

Fetches park data from the National Park Service API and returns it as a pandas DataFrame.

Arguments

  • None

Returns

  • pandas.DataFrame: Raw parks data from the API

Example

from national_parks import get_parks_data

df = get_parks_data()
print(df.head())

clean_parks(df)

Description

Cleans the raw parks dataset and creates new features such as description length and number of activities.

Arguments

  • df (pandas.DataFrame): Raw parks data

Returns

  • pandas.DataFrame: Cleaned parks dataset

Example

from national_parks import get_parks_data, clean_parks

df = get_parks_data()
clean_df = clean_parks(df)

summarize_parks(df)

Description

Generates summary statistics for a parks dataset.

Arguments

  • df (pandas.DataFrame): Processed parks dataset

Returns

  • Summary output (DataFrame or dictionary depending on implementation)

Example

from national_parks import summarize_parks
import pandas as pd

df = pd.read_csv("data/processed/parks_final.csv")
summary = summarize_parks(df)

print(summary)

top_parks_by_alerts(df)

Description

Returns the parks with the highest number of alerts.

Arguments

  • df (pandas.DataFrame): Processed parks dataset

Returns

  • pandas.DataFrame: Top parks sorted by alert count

Example

from national_parks import top_parks_by_alerts
import pandas as pd

df = pd.read_csv("data/processed/parks_final.csv")
top_parks = top_parks_by_alerts(df)

print(top_parks)

Notes

  • Data collection functions require an NPS API key stored in a .env file.
  • The dataset used in examples is located in data/processed/parks_final.csv.