Pandas DataFrame.resample() Function

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Pandas DataFrame.resample() Function

Author：JIYIK Last Updated：2025/05/01 Views：

Python Pandas DataFrame.resample() function resamples time series data.

`pandas.DataFrame.resample()`Syntax

DataFrame.resample(
    rule,
    axis=0,
    closed=None,
    label=None,
    convention="start",
    kind=None,
    loffset=None,
    base=None,
    on=None,
    level=None,
    origin="start_day",
    offset=None,
)

parameter


`rule`	It is an offset string or object representing the target transformation.
`axis`	It specifies which axis to use for up or down sampling. For `Series`, the default is 0, i.e. along the rows.
`closed`	It specifies which side of the bin interval is closed. It has two options: `right`or `left`.
`label`	It specifies the edge labels to `bin`label `bin`. It has two options: `right`or `left`.
`convention`	It has four options: `start`, `end`, `s`or `e`, and for PeriodIndex only, it uses `start`or `end`.
`kind`	It specifies the kind of index generated, with two options: Timestamp or Period. It has two options: `timestamp`or `period`. `timestamp`converts the generated index to a DateTimeIndex, while `period`converts it to a PeriodIndex.
`loffset`	It adjusts the time stamps for resampling.
`base`	It is an integer. Its default value is 0.
`on`	It indicates the name of the column to be used for resampling instead of the index. The column must be datetime-like.
`level`	It indicates the level name to use for resampling. Levels must be date-like.
`origin`	It is used to adjust the timestamp of the packet. It has three options: `epoch`, `start`or `start_day`.
`offset`	It represents `origin`the offset to be added to the parameter `timedelta`.

Return Value

It returns the resampled object.

Example code: `DataFrame.resample()`Method to resample series data by week

import pandas as pd

index = pd.date_range('1/1/2021', periods=30, freq='D')
series = pd.Series(range(30), index=index)
print("The Original Series is: \n")
print(series)

series1= series.resample('W').sum()
print("The Resampled Data is: \n")
print(series1)

Output:

The Original Series is: 

2021-01-01     0
2021-01-02     1
2021-01-03     2
2021-01-04     3
2021-01-05     4
2021-01-06     5
2021-01-07     6
2021-01-08     7
2021-01-09     8
2021-01-10     9
2021-01-11    10
2021-01-12    11
2021-01-13    12
2021-01-14    13
2021-01-15    14
2021-01-16    15
2021-01-17    16
2021-01-18    17
2021-01-19    18
2021-01-20    19
2021-01-21    20
2021-01-22    21
2021-01-23    22
2021-01-24    23
2021-01-25    24
2021-01-26    25
2021-01-27    26
2021-01-28    27
2021-01-29    28
2021-01-30    29
Freq: D, dtype: int64
The Resampled Data is: 

2021-01-03      3
2021-01-10     42
2021-01-17     91
2021-01-24    140
2021-01-31    159
Freq: W-SUN, dtype: int64

The function returns the sum of the resamples in weekly units.

Example code: `DataFrame.resample()`Method to resample `Series`data by month

import pandas as pd

index = pd.date_range('1/1/2021', periods=30, freq='D')
series = pd.Series(range(30), index=index)
print("The Original Series is: \n")
print(series)

series1= series.resample('M').sum()
print("The Resampled Data is: \n")
print(series1)

Output:

The Original Series is: 

2021-01-01     0
2021-01-02     1
2021-01-03     2
2021-01-04     3
2021-01-05     4
2021-01-06     5
2021-01-07     6
2021-01-08     7
2021-01-09     8
2021-01-10     9
2021-01-11    10
2021-01-12    11
2021-01-13    12
2021-01-14    13
2021-01-15    14
2021-01-16    15
2021-01-17    16
2021-01-18    17
2021-01-19    18
2021-01-20    19
2021-01-21    20
2021-01-22    21
2021-01-23    22
2021-01-24    23
2021-01-25    24
2021-01-26    25
2021-01-27    26
2021-01-28    27
2021-01-29    28
2021-01-30    29
Freq: D, dtype: int64
The Resampled Data is: 

2021-01-31    435
Freq: M, dtype: int64

The function returns the sum resampled by month.

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