Update README.md

README.md

@@ -17,6 +17,30 @@ pretty_name: USA options implied volatility features for machine learning
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+
+# Downloading the Options IV SP500 Dataset
+
+This document will guide you through the steps to download the Options IV SP500 dataset from Hugging Face Datasets. This dataset includes data on the options of the S&P 500, including implied volatility.
+
+To start, you'll need to install Hugging Face's `datasets` library if you haven't done so already. You can do this using the following pip command:
+
+```python
+!pip install datasets
+```
+
+Here's the Python code to load the Options IV SP500 dataset from Hugging Face Datasets and convert it into a pandas DataFrame:
+
+```python
+from datasets import load_dataset
+import pandas as pd
+
+id = "gauss314/options-IV-SP500"
+data_iv = load_dataset(id)
+df_iv = pd.DataFrame(data_iv['train'])
+```
+
+
+
 The dataset provided includes a variety of features and targets. In machine learning and predictive modeling, features are the input variables used to predict target variables, or the outcomes we're interested in predicting.
 
 The features in this dataset encompass all of the data columns except for DITM_IV, ITM_IV, sITM_IV, ATM_IV, sOTM_IV, OTM_IV, and DOTM_IV. These features include data on traded contracts, open interest, the spread of strike prices, and the number of different expiration dates, among others. These features can be used to understand the characteristics of the security's options and their trading activity.