This code creates a new column named **"TermRatio"** in the...

This code creates a new column named "TermRatio" in the pandas DataFrame crifDf_local, using a conditional logic provided by np.where, which is part of the NumPy library. Here's what it does:

• Logic:

  • It evaluates the condition: (crifDf_local.Label1 == '') & (crifDf_local.RiskType == 'Risk_Inflation')
    • If this condition is True, the value for the "TermRatio" column will be: crifDf_local.RemainingMaturity / crifDf_local.DaysToMaturity
    • If this condition is False, the value for the "TermRatio" column will be: crifDf_local.RemainingTenorDays / crifDf_local.TenorDaysHigh

• Breaking it down:

  1. (crifDf_local.Label1 == ''): Checks if the "Label1" column is an empty string.
  2. (crifDf_local.RiskType == 'Risk_Inflation'): Checks if the "RiskType" column contains the value 'Risk_Inflation'.
  3. Combines the two conditions with & (logical AND) to ensure both conditions are satisfied for the "True" branch.
  4. Based on the evaluated condition, the appropriate formula is applied to compute the value for the "TermRatio" column.

• Finally: The resulting values (after applying the condition) are stored as a new column called "TermRatio" in the crifDf_local DataFrame.

This operation essentially creates a calculated column in the dataframe based on a conditional formula.