sgfixedincome_pkg.consolidate

Functions

merge_dataframes(df_list)

Merges a list of DataFrames by appending rows, with validation of input.

create_banks_df(scrape_inputs)

Scrapes deposit rates from multiple bank websites and combines them into a single DataFrame.

add_ssb_details(df, current_ssb_holdings, issue_code)

Add additional details to the DataFrame with SSB tenure and rate data.

create_ssb_df(client[, current_ssb_holdings])

Create a dataframe containing the details and rates for the latest Singapore Savings Bond (SSB).

create_tbill_df(tbill_details)

Create a pandas DataFrame with details about a T-bill.

create_combined_df([scrape_inputs, ...])

Creates a combined DataFrame by aggregating data from banks, MAS Singapore Savings Bonds (SSBs),

Module Contents

sgfixedincome_pkg.consolidate.merge_dataframes(df_list)[source]

Merges a list of DataFrames by appending rows, with validation of input.

Parameters:

df_list (list of pd.DataFrame) – A list of pandas DataFrames to be merged. Each DataFrame must either be empty, or contain exactly the following columns: ‘Tenure’, ‘Rate’, ‘Deposit lower bound’, ‘Deposit upper bound’, ‘Required multiples’, ‘Product provider’, ‘Product’.

Returns:

A single DataFrame with all rows from the input DataFrames. Returns an empty DataFrame with the required columns if all input DataFrames are empty.

Return type:

pd.DataFrame

Raises:

  • TypeError – If the input is not a list or does not contain pandas DataFrames.

  • ValueError – If any DataFrame in the list does not have exactly the required columns.

sgfixedincome_pkg.consolidate.create_banks_df(scrape_inputs)[source]

Scrapes deposit rates from multiple bank websites and combines them into a single DataFrame.

Even if scraping fails for some websites, a DataFrame containing data from successfully scraped sites is still returned. The function also provides a list of dictionaries with information on websites it failed to scrape from. The function also validates the input before running its main task. If we fail to scrape from all websites, the function returns an empty dataframe.

Parameters:

scrape_inputs (list of tuples) –

Each tuple contains:

  • URL (str): The webpage to scrape.

  • Table class (str): The class of the table to locate.

  • Provider (str): The name of the bank/provider.

  • Required multiples (float or None, optional): Value to populate the “Required multiples” column. Defaults to None if omitted.

Returns:

A tuple containing:

  • pd.DataFrame: Combined DataFrame with all successfully scraped deposit rates.

  • list of dict: Each dict contains details of failed scrapes with:

    • product (str): Name of the provider and product that failed (e.g. DBS bank fixed deposit)

    • error (str): Error message describing the failure.

Return type:

tuple

Raises:

ValueError – If the input is not a list of tuples with the expected structure.

sgfixedincome_pkg.consolidate.add_ssb_details(df, current_ssb_holdings, issue_code)[source]

Add additional details to the DataFrame with SSB tenure and rate data.

Parameters:

  • df (pd.DataFrame) – DataFrame with SSB tenure month and rates.

  • current_ssb_holdings (float) – Current SSB holdings in Singapore dollars.

  • issue_code (str) – The SSB’s issue code.

Returns:

Updated DataFrame with additional SSB information.

Return type:

pd.DataFrame

sgfixedincome_pkg.consolidate.create_ssb_df(client, current_ssb_holdings=0.0)[source]

Create a dataframe containing the details and rates for the latest Singapore Savings Bond (SSB).

Parameters:

  • client – An initialized instance of the MAS_bondsandbills_APIClient.

  • current_ssb_holdings (float, optional) – The amount of SSBs you currently hold in Singapore dollars. Defaults to 0.0.

Returns:

A dataframe with SSB tenure rates and additional details.

Return type:

pandas.DataFrame

sgfixedincome_pkg.consolidate.create_tbill_df(tbill_details)[source]

Create a pandas DataFrame with details about a T-bill.

Parameters:

tbill_details (dict) –

A dictionary containing details about a T-bill. Expected keys include:

  • cutoff_yield (float): in percentage.

  • issue_code (str): identifies the T-bill.

  • auction_tenor (float): specifies if it is a 6-month (0.5) or 12-month (1.0) T-bill.

Returns:

A DataFrame with the following columns:

  • Tenure (int): The tenure of the T-bill in months.

  • Rate (float): The cutoff yield of the T-bill.

  • Deposit lower bound (int): The minimum investment amount (fixed at 1000).

  • Deposit upper bound (int): The maximum investment amount (fixed at 99999999).

  • Required multiples (int): The required investment increments (fixed at 1000).

  • Product provider (str): The provider of the product (fixed as “MAS”).

  • Product (str): A description of the T-bill, including its issue code.

Return type:

pd.DataFrame

Example

>>> tbill_details = {"cutoff_yield": 3.08, "issue_code": "BS24123F", "auction_tenor": 0.5}
>>> df = create_tbill_df(tbill_details)
>>> df
   Tenure  Rate  Deposit lower bound  Deposit upper bound  Required multiples Product provider          Product
0       6  3.08                 1000             99999999                1000              MAS  T-bill BS24123F
sgfixedincome_pkg.consolidate.create_combined_df(scrape_inputs=[('https://www.dbs.com.sg/personal/rates-online/fixed-deposit-rate-singapore-dollar.page', 'tbl-primary mBot-24', 'DBS'), ('https://www.uob.com.sg/personal/online-rates/singapore-dollar-time-fixed-deposit-rates.page', 'table__carousel-table', 'UOB'), ('https://www.ocbc.com/personal-banking/deposits/fixed-deposit-sgd-interest-rates.page', 'table__comparison-table', 'OCBC')], current_ssb_holdings=0.0, tbill_threshold=10)[source]

Creates a combined DataFrame by aggregating data from banks, MAS Singapore Savings Bonds (SSBs), and Treasury Bills (T-bills), and providing information on cases where data fetching failed.

Parameters:

  • scrape_inputs (list of tuples, optional) –

    Input parameters for scraping bank data. Each tuple contains:

    • URL (str): The webpage to scrape.

    • Table class (str): The class of the table to locate.

    • Provider (str): The name of the bank/provider.

    • Required multiples (float or None, optional): Value to populate the “Required multiples” column. Defaults to None if omitted.

    Default value includes DBS, UOB, and OCBC bank details.

  • current_ssb_holdings (float, optional) – The amount of SSBs you currently hold in Singapore dollars. Defaults to 0.0.

  • tbill_threshold (int, optional) – The threshold for the yield difference in basis points for the T-bill warning. Default is 10.

Returns:

A tuple containing:

  • pd.DataFrame: Combined DataFrame containing data from banks, SSBs, and T-bills.

  • list of dict: List of fetch failures, where each entry is a dictionary with two keys:

    • product: the product-provider pair (e.g., ‘MAS SSB’, ‘MAS T-bill’)

    • error: the error message.

  • list of str: List of warning messages generated during the process.

Return type:

tuple