pandas-datareader

$npx mdskill add mkurman/zorai/pandas-datareader

Fetch economic and financial time series from multiple data sources.

  • Retrieve GDP, inflation, and interest rate data for analysis.
  • Connects to FRED, World Bank, OECD, Eurostat, and Yahoo Finance.
  • Returns pandas DataFrames containing timestamped series values.
  • Supports custom date ranges and variable identifiers via code.

SKILL.md

.github/skills/pandas-datareaderView on GitHub ↗
---
name: pandas-datareader
description: "Multi-source financial data reader: FRED, World Bank, OECD, Eurostat, St. Louis Fed, Yahoo, Google, and more. Standard interface for economic and financial time series data ingestion."
tags: [financial-data, economic-data, fred, world-bank, time-series, python, zorai]
---
## Overview

pandas-datareader provides a unified interface for reading economic and financial time series from multiple sources: FRED (Federal Reserve), World Bank, OECD, Eurostat, Yahoo Finance, and St. Louis Fed. Standard tool for macroeconomic data ingestion.

## Installation

```bash
uv pip install pandas-datareader
```

## FRED Data

```python
import pandas_datareader.data as web
import datetime

start = datetime.datetime(2020, 1, 1)
gdp = web.DataReader("GDP", "fred", start)
unemp = web.DataReader("UNRATE", "fred", start)
cpi = web.DataReader("CPIAUCSL", "fred", start)
fedfunds = web.DataReader("FEDFUNDS", "fred", start)
ten_year = web.DataReader("DGS10", "fred", start)

import pandas as pd
combined = pd.DataFrame({"GDP": gdp["GDP"], "CPI": cpi["CPIAUCSL"], "FedFunds": fedfunds["FEDFUNDS"]})
print(combined.tail())
```

## World Bank

```python
gdp_pc = web.DataReader("NY.GDP.PCAP.CD", "worldbank", start=2015)
```

## References
- [pandas-datareader docs](https://pandas-datareader.readthedocs.io/)
- [FRED API](https://fred.stlouisfed.org/docs/api/fred/)

More from mkurman/zorai

SkillDescription
account-management>
agile-scrum>
albumentationsFast image augmentation library (Albumentations). 70+ transforms for classification, segmentation, object detection, keypoints, and pose estimation. Optimized OpenCV-based pipeline with unified API across all CV tasks. Supports images, masks, bounding boxes, and keypoints simultaneously. Note: classic Albumentations (MIT) is no longer maintained; successor AlbumentationsX uses AGPL-3.0. For torchvision-native augmentations, use torchvision.transforms.v2.
aml-complianceAnti-Money Laundering (AML) and Know Your Customer (KYC) compliance workflow. Sanctions screening, PEP detection, transaction monitoring, suspicious activity reporting (SAR), and OFAC compliance.
anki-connectThis skill is for interacting with Anki through AnkiConnect, and should be used whenever a user asks to interact with Anki, including to read or modify decks, notes, cards, models, media, or sync operations.
approval-checkpoint-long-taskCanonical long-task pack for daemon-managed work with deliberate approval checkpoints, status summaries, rollback notes, and mobile-safe governance-aware updates.
auditing-goal-artifactsUse when reviewing recent zorai goal run outputs, closure markers, ledgers, or evidence bundles to judge whether completion is credible or to identify remaining uncertainty.
autogenAutoGen (Microsoft) — multi-agent conversation framework. Agent-to-agent chat, code generation & execution, tool use, group chat, and human-in-the-loop. Build collaborative AI systems with specialized agents.
backtraderPython backtesting framework for trading strategies. Data feeds, brokers, analyzers, and live trading support. Strategy development with commission models, slippage, and signal-based execution.
beautiful-mermaidRender Mermaid diagrams as SVG and PNG using the Beautiful Mermaid library. Use when the user asks to render a Mermaid diagram.