Funciones básicas
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df = pd.read_csv("df.csv", parse_dates = ["col_name"]) Cargar csv y convertir una columna a formato de fecha
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df.to_period("M") Convert datetime index of dataframe to YYYY-MM
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pd.Timestamp("1/2/2019") |
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pd.Timestamp(2019, 2, 1) |
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pd.Timestamp(date(2019, 8, 26)) |
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pd.Timestamp(2019, 2, 1, 16, 17, 22) |
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pd.Timestamp(year = 2019, month = 10, day = 28, hour = 16, minute = 56, second = 12, microsecond = 13, nanosecond = 16) Convert something to Timestamp format
(YYYY-MM-DD HH:MM:SS)
Microseconds and nanoseconds appear as decimals in the seconds field
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d.year; d.month; d.day; d.minute; d.second; d.microsecond; d.nanosecond Timestamp attributes
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d.quarter; d.week; d.dayofweek; d.dayofyear; d.day_name(); d.month_name() Timestamp attributes that do calculations
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Period class
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p = pd.Period("2017-01") Basic Period creation
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p.start_time Period start time (with months: 1st day of month 00:00:00)
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p.end_time Period end time (with months: last day of month 23:59:59.999...)
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p.asfreq("D") Change period to days (called frequency) If a YYYY-MM period was given, new period is last day of month
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q = p.asfreq("M") Change period to months (called frequency) If a YYYY-MM-DD period was given, day is discarded and can't be retrieved.
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pd.Period("2018-05").to_timestamp() Period to timestamp
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p = pd.Period("2017-05-23") + 2 Add two days to period
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pd.Period("2017-05-23") - pd.Period("2017-05-28") Returns time difference in days (chosen frequency)
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Represents a period of time, not an instant. Months are the default period.
period_range class
p = pd.period_range(start = "2019-1-1T15:0:0", periods = 12, freq = "H") |
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Timedelta class
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d = pd.Timedelta(weeks = 1, days = 2, hours = 3, minutes = 4, seconds = 5, milliseconds = 6, microseconds = 7, nanoseconds = 8) |
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pd.Timedelta("1 day 1 millisecond") |
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pd.Timedelta("2.3 hours") Creation of Timedelta object
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d.days; d.seconds; d.microseconds; d.nanoseconds Timedelta attributes
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pd.Timestamp(2019, 8, 25, 18, 49) + pd.Timedelta("3 hours") Operations with timestamp
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Used for making operations with Timestamps (substraction, addition...)
date_range class
pd.date_range("August, 28 2018", periods = 5, freq = "M") |
pd.date_range("August, 28 2018", periods = 5, freq = "D") |
pd.date_range(start = date(2019, 8, 13), end = date(2019, 9, 21), freq = "W") |
pd.date_range(start = "2018-01-1", end = "2019-12-31", freq = "MS") |
from datetime import datetime |
pd.date_range(start = datetime.today(), periods = 5, freq = "H") |
pd.date_range(start = "2019-1-1", end = "2019-3-1", periods = 4) |
pd.date_range(start = "2019-8-1", end = "2019-8-31", freq = "B") |
pd.date_range(start = "2019-8-1", end = "2019-8-31", freq = "B") + pd.Timedelta("3 hours") |
Índices formados por secuencias de fechas (DatetimeIndex). El rango podrá venir definido por una fecha de comienzo, una fecha de finalización, un número de períodos y una frecuencia (por tres de estos cuatro parámetros).
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