📊 Central Bank of Russia Historical Currency Rates (1992-2026)
This dataset contains daily official exchange rates of foreign currencies against the Russian Ruble, published by the Central Bank of Russia (CBR). All rates are normalized to 1 unit of currency for easy analysis.
Use case: Database storage, filtering by currency, pivot operations
🚀 Usage Examples
Method 1: Direct Parquet Loading (Fastest! ⚡)
import pandas as pd
# Load wide format from Parquet
url_wide = "https://huggingface.co/datasets/TimeSeriesHub/cbr-historical-rates/resolve/main/cbr_rates_wide.parquet"
df_wide = pd.read_parquet(url_wide)
print("✅ Wide format loaded:")
print(df_wide.head())
# Load long format from Parquet
url_long = "https://huggingface.co/datasets/TimeSeriesHub/cbr-historical-rates/resolve/main/cbr_rates_long.parquet"
df_long = pd.read_parquet(url_long)
print("\n✅ Long format loaded:")
print(df_long.head())
Method 2: Using Hugging Face Datasets
from datasets import load_dataset
# Load wide format (default)
dataset_wide = load_dataset("TimeSeriesHub/cbr-historical-rates")
df_wide = dataset_wide["train"].to_pandas()
print(df_wide.head())
# Load long format
dataset_long = load_dataset("TimeSeriesHub/cbr-historical-rates", "long")
df_long = dataset_long["train"].to_pandas()
print(df_long.head())
📊 Basic Analysis Examples
# Convert date to datetime
df_wide['date'] = pd.to_datetime(df_wide['date'])
# Get USD rates
usd_rates = df_wide[['date', 'USD']]
print("USD rates (first 5):")
print(usd_rates.head())
# Calculate statisticsprint(f"\nUSD - Mean: {df_wide['USD'].mean():.2f}")
print(f"USD - Min: {df_wide['USD'].min():.2f}")
print(f"USD - Max: {df_wide['USD'].max():.2f}")
# Filter by year
df_2023 = df_wide[df_wide['date'].dt.year == 2023]
print(f"\n2023 data: {len(df_2023)} days")
@dataset{timeserieshub_cbr_2026,
title = {Central Bank of Russia Historical Currency Rates (1992-2026)},
author = {TimeSeriesHub},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/TimeSeriesHub/cbr-historical-rates}
}
