Warconomy
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Python

Consume Warconomy in Python with requests and pandas: load the dataset, filter to live observations, join to sources, and read a CSV distribution directly into a DataFrame. Static files only — no client to install beyond your usual stack. Not real-time.

static reference · data June 5, 2026

Use requests to fetch JSON and pandas to work with it. Load data.json into a DataFrame, filter to live observations, join to sources for citation, or read a CSV distribution directly. There is no Warconomy client to install — just your usual Python stack against static files.

  • requests + pandas; static files.
  • Filter to live rows before citing.
  • CSV distributions load straight into pandas.

Load the dataset

import requests, pandas as pd

data = requests.get("https://warconomy.com/datasets/conflict-economic-impact/data.json").json()
obs = pd.DataFrame(data["observations"])
live = obs[obs["dataMode"] == "live"]  # cite live values only

Join to sources

sources = pd.DataFrame(data["sources"]).set_index("id")["publisher"]
live = live.assign(publisher=live["sourceId"].map(sources))

Read a CSV distribution

# read a CSV distribution straight into pandas
df = pd.read_csv("https://warconomy.com/datasets/conflict-economic-impact/observations.csv")

More

R: /developers/r · CLI: /developers/cli · distributions: bundle.

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