Fix some missing docstrings

openbb_terminal/fixedincome/fred_model.py

@@ -21,6 +21,10 @@ from openbb_terminal.rich_config import console
 
 logger = logging.getLogger(__name__)
 
+ice_bofa_path = pathlib.Path(__file__).parent / "ice_bofa_indices.xlsx"
+commercial_paper_path = pathlib.Path(__file__).parent / "commercial_paper.xlsx"
+spot_rates_path = pathlib.Path(__file__).parent / "corporate_spot_rates.xlsx"
+
 YIELD_CURVE_SERIES_NOMINAL = {
     "1Month": "DGS1MO",
     "3Month": "DGS3MO",
@@ -655,7 +659,12 @@ def get_sofr(
     Parameters
     ----------
     parameter: str
-        The parameter to get data for.
+        The parameter to get data for. Choose from:
+            "overnight"
+            "30_day_average"
+            "90_day_average"
+            "180_day_average"
+            "index"
     start_date: Optional[str]
         Start date, formatted YYYY-MM-DD
     end_date: Optional[str]
@@ -705,7 +714,18 @@ def get_ameribor(
     Parameters
     ----------
     parameter: str
-        The parameter to get data for.
+        The parameter to get data for. Choose from:
+            "overnight": "AMERIBOR",
+            "term_30": "AMBOR30T",
+            "term_90": "AMBOR90T",
+            "1_week_term_structure": "AMBOR1W",
+            "1_month_term_structure": "AMBOR1M",
+            "3_month_term_structure": "AMBOR3M",
+            "6_month_term_structure": "AMBOR6M",
+            "1_year_term_structure": "AMBOR1Y",
+            "2_year_term_structure": "AMBOR2Y",
+            "30_day_ma": "AMBOR30",
+            "90_day_ma": "AMBOR90",
     start_date: Optional[str]
         Start date, formatted YYYY-MM-DD
     end_date: Optional[str]
@@ -730,7 +750,14 @@ def get_fed(
     Parameters
     ----------
     parameter: str
-        The parameter to get data for.
+        The parameter to get data for. Choose from:
+            "monthly"
+            "daily"
+            "weekly"
+            "daily_excl_weekend"
+            "annual"
+            "biweekly"
+            "volume"
     start_date: Optional[str]
         Start date, formatted YYYY-MM-DD
     end_date: Optional[str]
@@ -830,7 +857,12 @@ def get_dwpcr(
     Parameters
     ----------
     parameter: str
-        The parameter to get data for.
+        The parameter to get data for. Choose from:
+            "daily_excl_weekend"
+            "monthly"
+            "weekly"
+            "daily"
+            "annual"
     start_date: Optional[str]
         Start date, formatted YYYY-MM-DD
     end_date: Optional[str]
@@ -859,7 +891,10 @@ def get_ecb(
     Parameters
     ----------
     interest_type: Optional[str]
-        The ability to decide what interest rate to plot
+        The ability to decide what interest rate to plot. Choose from:
+            "deposit"
+            "lending"
+            "refinancing"
     start_date: Optional[str]
         Start date, formatted YYYY-MM-DD
     end_date: Optional[str]
@@ -919,6 +954,18 @@ def get_usrates(
         Either "tbills", "cmn", or "tips".
     maturity: str
         Depending on the chosen parameter, a set of maturities is available.
+            "4_week": {"tbill": "DTB4WK"},
+            "1_month": {"cmn": "DGS1MO"},
+            "3_month": {"tbill": "TB3MS", "cmn": "DGS3MO"},
+            "6_month": {"tbill": "DTB6", "cmn": "DGS6MO"},
+            "1_year": {"tbill": "DTB1YR", "cmn": "DGS1"},
+            "2_year": {"cmn": "DGS2"},
+            "3_year": {"cmn": "DGS3"},
+            "5_year": {"tips": "DFII5", "cmn": "DGS5"},
+            "7_year": {"tips": "DFII7", "cmn": "DGS7"},
+            "10_year": {"tips": "DFII10", "cmn": "DGS10"},
+            "20_year": {"tips": "DFII20", "cmn": "DGS20"},
+            "30_year": {"tips": "DFII30", "cmn": "DGS30"},
     start_date: Optional[str]
         Start date, formatted YYYY-MM-DD
     end_date: Optional[str]
@@ -935,11 +982,14 @@ def get_icebofa(
     category: str = "all",
     area: str = "us",
     grade: str = "non_sovereign",
+    options: bool = False,
     start_date: Optional[str] = None,
     end_date: Optional[str] = None,
 ) -> pd.DataFrame:
     """Get data for ICE BofA US Corporate Bond Indices.
 
+    Find the available options by using the options parameter.
+
     Parameters
     ----------
     data_type: str
@@ -951,15 +1001,37 @@ def get_icebofa(
     grade: str
         The type of grade you want to see, either "a", "aa", "aaa", "b", "bb", "bbb", "ccc", "crossover",
         "high_grade", "high_yield", "non_financial", "non_sovereign", "private_sector", "public_sector"
+    options: bool
+        Set to True to obtain the available options.
     start_date: Optional[str]
         Start date, formatted YYYY-MM-DD
     end_date: Optional[str]
         End date, formatted YYYY-MM-DD
     """
+    series = pd.read_excel(ice_bofa_path)
+
+    if options:
+        return series.drop(
+            ["Frequency", "Units", "Asset Class", "FRED Series ID", "Description"],
+            axis=1,
+        )[
+            series["Type"].isin(
+                ["yield", "yield_to_worst", "total_return"]
+                if data_type != "spread"
+                else ["spread"]
+            )
+        ]
+
     if data_type == "total_return":
         units = "index"
     elif data_type in ["yield", "yield_to_worst", "spread"]:
         units = "percent"
+    else:
+        console.print(
+            "Please choose either 'yield', 'yield_to_worst', "
+            "'total_return' or 'spread'."
+        )
+        return pd.DataFrame()
 
     series = pd.read_excel(ice_bofa_path)
     series = series[
@@ -1025,7 +1097,7 @@ def get_cp(
     start_date: Optional[str] = None,
     end_date: Optional[str] = None,
 ):
-    """Plot Commercial Paper
+    """Obtain Commercial Paper data
 
     Parameters
     ----------
@@ -1082,7 +1154,7 @@ def get_spot(
     Parameters
     ----------
     maturity: str
-        The maturity you want to see (ranging from '1y' to '100y')
+        The maturity you want to see (ranging from '1y' to '100y' in interval of 0.5, e.g. '50.5y')
     category: list
         The category you want to see ('par_yield' and/or 'spot_rate')
     description: bool
@@ -1113,7 +1185,7 @@ def get_spot(
 
     df = pd.DataFrame.from_dict(series_dictionary)
     df.index = pd.to_datetime(df.index).date
-    return df
+    return df[0]
 
 
 def get_hqm(
@@ -1178,6 +1250,7 @@ def get_icespread(
     category: str = "all",
     area: str = "us",
     grade: str = "non_sovereign",
+    options: bool = False,
     start_date: Optional[str] = None,
     end_date: Optional[str] = None,
 ) -> pd.DataFrame:
@@ -1198,6 +1271,7 @@ def get_icespread(
         category=category,
         area=area,
         grade=grade,
+        options=options,
         start_date=start_date,
         end_date=end_date,
     )

openbb_terminal/fixedincome/oecd_model.py

@@ -193,8 +193,36 @@ def get_treasury(
     start_date: Optional[str] = None,
     end_date: Optional[str] = None,
 ) -> pd.DataFrame:
-    df_short, df_long = pd.DataFrame(), pd.DataFrame()
+    """Gets interest rates data from selected countries (3 month and 10 year)
 
+    Short-term interest rates are the rates at which short-term borrowings are effected between financial
+    institutions or the rate at which short-term government paper is issued or traded in the market. Short-term
+    interest rates are generally averages of daily rates, measured as a percentage. Short-term interest rates are
+    based on three-month money market rates where available. Typical standardised names are "money market rate" and
+    "treasury bill rate".
+
+    Long-term interest rates refer to government bonds maturing in ten years. Rates are mainly determined by the
+    price charged by the lender, the risk from the borrower and the fall in the capital value. Long-term interest
+    rates are generally averages of daily rates, measured as a percentage. These interest rates are implied by the
+    prices at which the government bonds are traded on financial markets, not the interest rates at which the loans
+    were issued. In all cases, they refer to bonds whose capital repayment is guaranteed by governments. Long-term
+    interest rates are one of the determinants of business investment. Low long-term interest rates encourage
+    investment in new equipment and high interest rates discourage it. Investment is, in turn, a major source of
+    economic growth.
+
+    Parameters
+    ----------
+    short_term: list
+        Countries you wish to plot the 3-month interest rate for
+    long_term: list
+        Countries you wish to plot the 10-year interest rate for
+    forecast: bool
+        If True, plot forecasts for short term interest rates
+    start_date: str
+        Start date of data, in YYYY-MM-DD format
+    end_date: str
+        End date of data, in YYYY-MM-DD format
+    """
     if short_term:
         df_short = get_interest_rate_data(
             f"short{'_forecast' if forecast else ''}",

openbb_terminal/fixedincome/oecd_view.py

@@ -54,14 +54,18 @@ def plot_treasuries(
 
     Parameters
     ----------
-    countries: list
-        List of countries to get data for
+    short_term: list
+        Countries you wish to plot the 3-month interest rate for
+    long_term: list
+        Countries you wish to plot the 10-year interest rate for
     forecast: bool
         If True, plot forecasts for short term interest rates
     start_date: str
         Start date of data, in YYYY-MM-DD format
     end_date: str
         End date of data, in YYYY-MM-DD format
+    raw: bool
+        If True, print raw data
     export: str
         Export data to csv or excel file
     external_axes: Optional[List[plt.Axes]]