In this post you can find how to:

  • solve error: ValueError: is a non-fixed frequency
  • floor, ceil or round to year, month or week in Pandas

(1) Get year, month or week in Pandas

df['year'] = df['date'].dt.year
df['month'] = df['date'].dt.month
df['day'] = df['date'].dt.week

(2) Round or floor year in Pandas

df['date'].dt.to_period('Y').dt.start_time

result:

0   2021-01-01
1   2022-01-01
2   2023-01-01
3   2024-01-01
Name: date, dtype: datetime64[ns]

(3) Round or floor year in Pandas

df['date'].dt.to_period('Y').dt.end_time

result:

0   2021-12-31 23:59:59.999999999
1   2022-12-31 23:59:59.999999999
2   2023-12-31 23:59:59.999999999
3   2024-12-31 23:59:59.999999999
Name: date, dtype: datetime64[ns]

(4) Round or floor year in Pandas

df['date'].dt.to_period('W-SUN').dt.start_time

result:

0   2020-12-28
1   2022-06-27
2   2023-03-27
3   2024-10-28
Name: date, dtype: datetime64[ns]

(5) Get Weekly Period in Pandas

df['date'].dt.to_period('W-SUN')

result:

0    2020-12-28/2021-01-03
1    2022-06-27/2022-07-03
2    2023-03-27/2023-04-02
3    2024-10-28/2024-11-03
Name: date, dtype: period[W-SUN]

(6) Ceil or floor by offests

(df['date'] + pd.offsets.YearBegin(-1)).dt.date
df['date'] + pd.offsets.MonthBegin(-1)

result:

0    2020-01-01
1    2022-01-01
2    2023-01-01
3    2024-01-01
Name: date, dtype: object

ValueError: is a non-fixed frequency

There is open issue about using dt.ceil, dt.floor, dt.round with coarser target frequencies:

  • YE
  • ME
  • W

Can't use dt.ceil, dt.floor, dt.round with coarser target frequencies

Usually you will receive error like:

  • ValueError: <30 * YearEnds: month=12> is a non-fixed frequency
  • ValueError: <YearEnd: month=12> is a non-fixed frequency
  • ValueError: <MonthEnd> is a non-fixed frequency
  • ValueError: <Week: weekday=6> is a non-fixed frequency

To solve this error you can:

  • get the period by: df['date'].dt.to_period('W-SUN')
  • get the start or the end of the period: .dt.start_time or .dt.end_time

Sample Data

import pandas as pd

data = {
    'date': [
        pd.Timestamp('2021-01-01 11:04:45'),
        pd.Timestamp('2022-07-01 12:035:15'),
        pd.Timestamp('2023-04-01 12:16:30'),
        pd.Timestamp('2024-11-01 15:57:59')
    ]
}

df = pd.DataFrame(data)
df