70 lines
2.3 KiB
Python
70 lines
2.3 KiB
Python
"""
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=== FinanceToolkit - Lesson 4: Economics Data & Exporting Results ===
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This script shows you how to:
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1. Access macroeconomic data (GDP, CPI, unemployment)
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2. Export any DataFrame to CSV or Excel for further use
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Run this file: python 04_economics_and_export.py
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"""
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from financetoolkit import Toolkit
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API_KEY = "wybWEsp1oB9abHfz3yPpQYwffxaN21B7"
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companies = Toolkit(
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tickers=["AAPL"],
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api_key=API_KEY,
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start_date="2020-01-01",
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)
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# ── 1. Unemployment Rates ─────────────────────────────────────────────
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print("=" * 60)
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print("UNEMPLOYMENT RATES")
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print("=" * 60)
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unemployment = companies.economics.get_unemployment_rate()
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print(unemployment.head(10))
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print()
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# ── 2. Consumer Price Index (CPI) ────────────────────────────────────
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print("=" * 60)
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print("CONSUMER PRICE INDEX (CPI)")
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print("=" * 60)
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cpi = companies.economics.get_consumer_price_index()
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print(cpi.head(10))
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print()
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# ── 3. GDP ────────────────────────────────────────────────────────────
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print("=" * 60)
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print("GROSS DOMESTIC PRODUCT (GDP)")
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print("=" * 60)
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gdp = companies.economics.get_gross_domestic_product()
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print(gdp.head(10))
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print()
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# ── 4. Exporting Data ────────────────────────────────────────────────
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# Any DataFrame can be saved to CSV or Excel for use in reports,
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# other tools, or further analysis.
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# Export historical data to CSV
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historical = companies.get_historical_data()
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historical.to_csv("aapl_historical_data.csv")
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print("[SAVED] aapl_historical_data.csv")
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# Export income statement to Excel
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income = companies.get_income_statement()
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income.to_excel("aapl_income_statement.xlsx")
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print("[SAVED] aapl_income_statement.xlsx")
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# Export ratios to CSV
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ratios = companies.ratios.collect_profitability_ratios()
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ratios.to_csv("aapl_profitability_ratios.csv")
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print("[SAVED] aapl_profitability_ratios.csv")
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print()
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print("[DONE] Your data has been exported. Open the CSV/Excel files")
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print(" in Excel, Google Sheets, or any data analysis tool.")
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