A time-series data processing device comprising: an event waveform extracting unit adapted to extract waveform data, estimated to change because of an event having occurred in a subject equipment, from each of a plurality of first time-series data sequentially observed over time from the subject equipment, wherein the event waveform extracting unit is adapted to extract the waveform data on a basis of a combination of partial string data whose values continuously increase or decrease in the first time-series data; a co-occurrence rate calculating unit adapted to calculate a co-occurrence rate of the waveform data extracted by the event waveform extracting unit among the first time-series data; a grouping unit adapted to classify the first the time-series data into groups depending on the co-occurrence rate of the waveform data calculated by the co-occurrence rate calculating unit; an event information generating unit adapted to determine time at which periods of occurrence of the waveform data overlap with each other among the first time-series data included in a group into which the first time-series data are classified by the grouping unit, and to generate event information identifying an event related to the waveform data on a basis of the determined time; a time-series data acquiring unit adapted to acquire second time-series data observed by a sensor provided in the subject equipment when determining abnormality of the subject equipment; a detecting unit adapted to detect outlier data from the second time-series data, the outlier data being partial string data falling within an abnormality range; and a determining unit adapted to determine abnormality of the subject equipment on a basis of the outlier data detected by the detecting unit and the event information generated by the event information generating unit. an event waveform extracting unit adapted to extract waveform data, estimated to change because of an event having occurred in a subject equipment, from each of a plurality of first time-series data sequentially observed over time from the subject equipment, wherein the event waveform extracting unit is adapted to extract the waveform data on a basis of a combination of partial string data whose values continuously increase or decrease in the first time-series data; a co-occurrence rate calculating unit adapted to calculate a co-occurrence rate of the waveform data extracted by the event waveform extracting unit among the first time-series data; a grouping unit adapted to classify the first the time-series data into groups depending on the co-occurrence rate of the waveform data calculated by the co-occurrence rate calculating unit; an event information generating unit adapted to determine time at which periods of occurrence of the waveform data overlap with each other among the first time-series data included in a group into which the first time-series data are classified by the grouping unit, and to generate event information identifying an event related to the waveform data on a basis of the determined time; a time-series data acquiring unit adapted to acquire second time-series data observed by a sensor provided in the subject equipment when determining abnormality of the subject equipment; a detecting unit adapted to detect outlier data from the second time-series data, the outlier data being partial string data falling within an abnormality range; and a determining unit adapted to determine abnormality of the subject equipment on a basis of the outlier data detected by the detecting unit and the event information generated by the event information generating unit.