資料分析之pandas.date_range
摘要：
def date_range(start=None, end=None, periods=None, freq=None, tz=None,
normalize=False, name=None, closed=None, **kwargs):
引數:
...
def date_range(start=None, end=None, periods=None, freq=None, tz=None, normalize=False, name=None, closed=None, **kwargs):
引數:
- start 開始時間
- end 結束時間
- periods 固定日期範圍，整數
-
normalize 若引數為
True表示將start、end引數值正則化到午夜時間戳 - name 生成時間索引物件名稱
-
freq 日期偏移量，預設為
D
| 別名 | 偏移量 | 說明 |
|---|---|---|
| D/d | Day | 每日曆日 |
| B | BusinessDay | 每工作日 |
| H/h | Hour | 每小時 |
| T或min | Minute | 每分 |
| S | Secend | 每秒 |
| L或ms | Milli | 每毫秒(每千分之一秒) |
| U | Micro | 每微秒(即百萬分之一秒) |
| M | MonthEnd | 每月最後一個日曆日 |
| BM | BusinessDayEnd | 每月最後一個工作 |
例1
import pandas as pd dates = pd.date_range(start="2018-10-01", end="2018-10-12") dates1 = pd.date_range(start="2018-10-01", periods=6) print(dates) print(dates1) DatetimeIndex(['2018-10-01', '2018-10-02', '2018-10-03', '2018-10-04', '2018-10-05', '2018-10-06', '2018-10-07', '2018-10-08', '2018-10-09', '2018-10-10', '2018-10-11', '2018-10-12'], dtype='datetime64[ns]', freq='D') DatetimeIndex(['2018-10-01', '2018-10-02', '2018-10-03', '2018-10-04', '2018-10-05', '2018-10-06'], dtype='datetime64[ns]', freq='D')
例2
import pandas as pd dates = pd.date_range(start="2018-10-01", periods=8, freq="B") dates1 = pd.date_range(start="2018-10-01", periods=8, freq="H") dates2 = pd.date_range(start="2018-10-01", periods=8, freq="S") print(dates) print(dates1) print(dates2) DatetimeIndex(['2018-10-01', '2018-10-02', '2018-10-03', '2018-10-04', '2018-10-05', '2018-10-08', '2018-10-09', '2018-10-10'], dtype='datetime64[ns]', freq='B') DatetimeIndex(['2018-10-01 00:00:00', '2018-10-01 01:00:00', '2018-10-01 02:00:00', '2018-10-01 03:00:00', '2018-10-01 04:00:00', '2018-10-01 05:00:00', '2018-10-01 06:00:00', '2018-10-01 07:00:00'], dtype='datetime64[ns]', freq='H') DatetimeIndex(['2018-10-01 00:00:00', '2018-10-01 00:00:01', '2018-10-01 00:00:02', '2018-10-01 00:00:03', '2018-10-01 00:00:04', '2018-10-01 00:00:05', '2018-10-01 00:00:06', '2018-10-01 00:00:07'], dtype='datetime64[ns]', freq='S')
例3
import pandas as pd dates = pd.date_range(start="2018-10-01 03:00:00", periods=8, freq="H", normalize=True) dates1 = pd.date_range(start="2018-10-01 03:00:00", periods=8, freq="H", normalize=False) print(dates) print(dates1) DatetimeIndex(['2018-10-01 00:00:00', '2018-10-01 01:00:00', '2018-10-01 02:00:00', '2018-10-01 03:00:00', '2018-10-01 04:00:00', '2018-10-01 05:00:00', '2018-10-01 06:00:00', '2018-10-01 07:00:00'], dtype='datetime64[ns]', freq='H') DatetimeIndex(['2018-10-01 03:00:00', '2018-10-01 04:00:00', '2018-10-01 05:00:00', '2018-10-01 06:00:00', '2018-10-01 07:00:00', '2018-10-01 08:00:00', '2018-10-01 09:00:00', '2018-10-01 10:00:00'], dtype='datetime64[ns]', freq='H')