Unprecedented dynamic phenomena appear in power grids due to integration of more and more inverter-based resources (IBR). A major challenge is that inverter models are proprietary information and usually only real code models are provided to grid operators. Thus, measurement based characterization of IBR is a popular approach to find the frequency-domain measurements of an IBR's admittance or impedance. The predominant methods rely on injecting perturbation and extracting frequency-domain information via fast Fourier transform (FFT). The goal of this research is to design time-domain measurement-based admittance identification methods so that event data can be utilized for online admittance identification. The proposed method has a key step: converting $dq$ -frame voltage and current transient responses into $s$ -domain expressions using eigensystem realization algorithm (ERA) or dynamic mode decomposition (DMD). From there, $s$ -domain admittance or frequency-domain admittance measurement will be computed. Proof of concept is first demonstrated using the data generated from an analytical model representing a grid-integrated IBR. The identified admittance is shown to be the exact match of the known admittance in the subsynchronous frequency range. The identified $s$ -domain admittance is employed for eigenvalue analysis and accurate stability prediction can be made. The tool is then tested on two electromagnetic transient (EMT) computer simulation testbeds: a PV grid-integration system and a type-4 wind grid-integration system. In the first case, offline admittance identification is demonstrated. In the second case, online admittance identification using data from two events is demonstrated.