PERF: Datetime/Timestamp.normalize for timezone naive datetimes by mroeschke · Pull Request #23634 · pandas-dev/pandas (original) (raw)

(bamboo-dev) jreback@dev:~/pandas-dev$ grep -r 86400 pandas/_libs/ --include '*.pyx'
pandas/_libs/tslibs/period.pyx:        {1, 24, 1440, 86400, 86400000, 86400000000, 86400000000000},
pandas/_libs/tslibs/period.pyx:        seconds = unix_date * 86400 + dts.hour * 3600 + dts.min * 60 + dts.sec
pandas/_libs/tslibs/period.pyx:        abstime += 86400
pandas/_libs/tslibs/period.pyx:    while abstime >= 86400:
pandas/_libs/tslibs/period.pyx:        abstime -= 86400
pandas/_libs/tslibs/period.pyx:    # abstime >= 0.0 and abstime <= 86400
pandas/_libs/tslibs/conversion.pyx:cdef int64_t DAY_NS = 86400000000000LL
pandas/_libs/tslibs/timedeltas.pyx:cdef int64_t DAY_NS = 86400000000000LL
pandas/_libs/tslibs/timedeltas.pyx:        m = 1000000000L * 86400 * 7
pandas/_libs/tslibs/timedeltas.pyx:        m = 1000000000L * 86400
pandas/_libs/tslibs/timedeltas.pyx:        86400000000042
pandas/_libs/tslibs/fields.pyx:    micros = np.mod(dtindex, 86400000000000, dtype=np.int64) // 1000LL
pandas/_libs/tslibs/src/datetime/np_datetime.c:    npy_int64 DAY_NS = 86400000000000LL;