Enhance documentation by adding argument descriptions to functions in historic_vol, pivots, reduce_df, and update_df modules

src/panel/historic_vol.rs

@@ -248,7 +248,7 @@ fn get_period_indices(
 }
 
 /// Calculate historic volatility.
-/// Arguments:
+/// # Arguments:
 /// - `df`: A Quantamental DataFrame.
 /// - `xcat`: The category to calculate the historic volatility for.
 /// - `cids`: A list of cross-sections. If none are provided, all cross-sections available

src/panel/mod.rs

@@ -1,3 +1,3 @@
 pub mod historic_vol;
-
+pub mod linear_composite;
 

src/utils/qdf/pivots.rs

@@ -19,7 +19,12 @@ fn get_ticker_from_qdf(df: &DataFrame) -> Result<String, Box<dyn Error>> {
     Ok(ticker)
 }
 
-/// Pivots a dataframe to a format where each ticker a column.
+/// Pivots a dataframe to a format where each ticker is a column.
+/// # Arguments:
+/// * `df` - The dataframe to pivot.
+/// * `metric` - The metric to pivot on. If None, defaults to "value".
+/// # Returns:
+/// * `DataFrame` - The pivoted dataframe.
 #[allow(dead_code)]
 pub fn pivot_dataframe_by_ticker(
     df: DataFrame,
@@ -67,6 +72,11 @@ pub fn pivot_dataframe_by_ticker(
 }
 
 /// Pivot ticker dataframe to qdf.
+/// # Arguments:
+/// * `df` - The dataframe to pivot.
+/// * `metric` - The metric to pivot on. If None, defaults to "value".
+/// # Returns:
+/// * `DataFrame` - The pivoted dataframe.
 #[allow(dead_code)]
 pub fn pivot_wide_dataframe_to_qdf(
     df: DataFrame,
@@ -102,6 +112,11 @@ pub fn pivot_wide_dataframe_to_qdf(
 }
 
 /// Splits a dataframe by ticker.
+/// # Arguments:
+/// * `df` - The dataframe to split.
+/// * `metrics` - The metrics to split on. If None, defaults to all metrics.
+/// # Returns:
+/// * `HashMap<String, DataFrame>` - A hashmap where the key is the ticker and the value is the dataframe.
 #[allow(dead_code)]
 fn split_df_by_tickers(
     df: &DataFrame,
@@ -146,6 +161,10 @@ fn split_df_by_tickers(
 
 /// Splits a QDF container data for a single ticker into a Vec of DataFrames (one per metric).
 /// The resulting DataFrames will have the "real_date" column and the metric column.
+/// # Arguments:
+/// * `df` - The dataframe to split.
+/// # Returns:
+/// * `Vec<DataFrame>` - A vector of dataframes, each containing the "real_date" and a metric column.
 #[allow(dead_code)]
 fn single_ticker_qdf_to_timeseries(mut df: DataFrame) -> Result<Vec<DataFrame>, Box<dyn Error>> {
     let mut df_vec = Vec::new();

src/utils/qdf/reduce_df.rs

@@ -7,6 +7,7 @@ use std::error::Error;
 const QDF_INDEX_COLUMNS: [&str; 3] = ["real_date", "cid", "xcat"];
 
 /// Filter a dataframe based on the given parameters.
+/// # Arguments:
 /// - `cids`: Filter by cross-sectional identifiers
 /// - `xcats`: Filter by extended categories
 /// - `metrics`: Filter by metrics

src/utils/qdf/update_df.rs

@@ -5,8 +5,10 @@ use std::error::Error;
 const QDF_INDEX_COLUMNS: [&str; 3] = ["real_date", "cid", "xcat"];
 
 /// Update a Quantamental DataFrame with new data.
+/// # Arguments:
 /// - `df`: The original DataFrame
 /// - `df_add`: The new DataFrame to add
+/// - `xcat_replace`: !NOT IMPLEMENTED! If true, replace existing xcats with new ones.
 ///
 pub fn update_dataframe(
     df: &DataFrame,