Download -18 - Sensational Janine -1976- Unrate... May 2026

Below is a complete, reusable script that:

#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
download_unrate_1976.py
----------------------
Fetches the U.S. unemployment‑rate (UNRATE) for 1976 from FRED
and saves it as:
    -18 - Sensational Janine -1976- UNRATE.csv
"""
import os
import sys
import requests
import pandas as pd
# ----------------------------------------------------------------------
# CONFIGURATION ---------------------------------------------------------
# ----------------------------------------------------------------------
API_KEY = os.getenv("FRED_API_KEY")          # set this env‑var or edit below
if not API_KEY:
    # If you don't want to use env‑var, hard‑code your key (not recommended):
    # API_KEY = "YOUR_32_CHAR_KEY"
    sys.exit("Error: Please set the environment variable FRED_API_KEY with your FRED API key.")
SERIES_ID = "UNRATE"
START_DATE = "1976-01-01"
END_DATE   = "1976-12-31"
OUTPUT_PATH = os.path.join(
    os.path.expanduser("~/Data/Unemployment"),
    "-18 - Sensational Janine -1976- UNRATE.csv"
)
# ----------------------------------------------------------------------
# FUNCTION -------------------------------------------------------------
# ----------------------------------------------------------------------
def fetch_unrate(api_key: str) -> pd.DataFrame:
    """
    Calls the FRED observations endpoint and returns a DataFrame.
    """
    endpoint = "https://api.stlouisfed.org/fred/series/observations"
    params = 
        "series_id": SERIES_ID,
        "api_key": api_key,
        "observation_start": START_DATE,
        "observation_end": END_DATE,
        "frequency": "m",
        "file_type": "json"   # easier to parse than CSV for pandas
response = requests.get(endpoint, params=params, timeout=10)
    response.raise_for_status()
    raw = response.json()
# Convert the list of dicts into a tidy DataFrame
    df = pd.DataFrame(raw["observations"])
    df = df[["date", "value"]].rename(columns="date": "DATE", "value": "UNRATE")
    # Convert numeric column; missing values are represented as '.' in FRED
    df["UNRATE"] = pd.to_numeric(df["UNRATE"], errors="coerce")
    return df
# ----------------------------------------------------------------------
# MAIN -----------------------------------------------------------------
# ----------------------------------------------------------------------
def main():
    # 1️⃣ fetch data
    df = fetch_unrate(API_KEY)
# 2️⃣ ensure output directory exists
    os.makedirs(os.path.dirname(OUTPUT_PATH), exist_ok=True)
# 3️⃣ write to CSV (no index, UTF‑8)
    df.to_csv(OUTPUT_PATH, index=False, encoding="utf-8")
    print(f"✅ Saved len(df) rows to OUTPUT_PATH")
if __name__ == "__main__":
    main()

How to run

# 1. Export your API key (once per session)
export FRED_API_KEY="YOUR_32_CHAR_KEY"
# 2. Ensure required packages are installed
pip install pandas requests
# 3. Execute the script
python download_unrate_1976.py

The script will create the folder ~/Data/Unemployment/ if it does not exist and place the file there with the exact name you specified.

| Item | Description | |------|-------------| | Data source | Federal Reserve Economic Data (FRED) – series UNRATE (Civilian Unemployment Rate, % of labor force) | | Time period | Calendar year 1976 (Jan 1 1976 – Dec 31 1976) | | File name you want | -18 - Sensational Janine -1976- UNRATE.csv (or any other extension you prefer) | | Typical use‑cases | Economic research, visualisations, teaching, building models, archiving historical macro data. |

The guide covers three ways to get the data:

Choose the method that best fits your workflow.

import pandas as pd
df = pd.read_csv('Download -18 - Sensational Janine -1976- UNRATE.csv')
df.head()
df.info()

df['DATE'] = pd.to_datetime(df['DATE'])
df = df.sort_values('DATE').set_index('DATE')

df_q = df.resample('Q').mean()

df['UNRATE'].plot(); df['UNRATE'].rolling(12).mean().plot()

df['mom'] = df['UNRATE'].pct_change()
df['yoy'] = df['UNRATE'].pct_change(12)

df.to_csv('UNRATE_cleaned.csv')

If you want, I can:

Related search suggestions will be prepared next.

It looks like you’ve pasted part of a filename or search query referencing "Sensational Janine" (1976) and an apparent download link with “-18” and “UNRATE.”

A few important points:

If you clarify what you’re actually trying to do (e.g., identify the film, find legal info about it, discuss its production), I’ll be glad to help within those boundaries.

Report: Unrated Film "Sensational Janine" (1976)

The file name or search query "Download -18 - Sensational Janine -1976- UNRATE..." suggests that the user is looking for an unrated film titled "Sensational Janine" released in 1976. Here's a brief report on this film: Download -18 - Sensational Janine -1976- UNRATE...

Unfortunately, I couldn't find more information on this film, including its genre, plot, cast, or crew. It's possible that it's a lesser-known or obscure film.

Possible Contexts:

Recommendations:

| What you need | Why it matters | |---------------|----------------| | Internet connection | To reach the FRED servers. | | Web browser (Chrome, Firefox, Edge, Safari) | For manual download. | | FRED API key (optional but recommended for API & script usage) | Allows higher request limits and avoids throttling. | | Python 3.9+ (if you choose the Python route) with pandas, pandas-datareader, requests installed. | | R 4.2+ (if you choose the R route) with the fredr package installed. | | A folder where you want the file saved – e.g., C:\Data\Unemployment\ or ~/Downloads/UNRATE/. | So the custom file name can be placed exactly where you want it. |

Getting an API key (one‑time step):

If you need to report on the status, integrity, or metrics of a file download for general purposes, you can use the following structure: Below is a complete, reusable script that:

REPORT: File Download Verification & Integrity Analysis

1. Executive Summary

2. Download Metrics

3. Integrity Check

4. Playback/Execution Test (If applicable)

5. Conclusion The file was successfully downloaded and verified. No corruption was detected during the transfer process. How to run # 1

If you need to repeat the download (e.g., for automation, batch jobs, or version control), the API is the cleanest route.

curl -L "https://api.stlouisfed.org/fred/series/observations?series_id=UNRATE&api_key=YOUR_API_KEY&observation_start=1976-01-01&observation_end=1976-12-31&frequency=m&file_type=csv" \
    -o "-18 - Sensational Janine -1976- UNRATE.csv"

Notes