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Pandas DataFrame Resample

Learn about the Pandas dataframe resample, its concept with examples.
Submitted by Pranit Sharma, on September 17, 2022

Pandas is a special tool that allows us to perform complex manipulations of data effectively and efficiently. Inside pandas, we mostly deal with a dataset in the form of DataFrame. DataFrames are 2-dimensional data structures in pandas. DataFrames consist of rows, columns, and data.

Python DataFrame.resample() Method

Pandas DataFrame.resample() method is used for time series data. A time series is a series of data points that are listed or ranked in time order. Most commonly, a time series can also be considered as a sequence defined at continuous equally spaced points in time.

It is an appropriate method for frequency conversion and resampling of time series.

Syntax

The syntax of DataFrame.resample() method is:

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
    )

Parameters

The parameters of DataFrame.resample() method are:

• rule: Target conversion
• axis: Column-wise or row-wise
• closed: Right or left boundary
• label: Right or left label
• convention: For PeriodIndex only, controls whether to use the start or end of rule.
• kind: Pass 'timestamp' to convert the resulting index to a DateTimeIndex or 'period' to convert it to a PeriodIndex. By default the input representation is retained.
• loffset: adjustments
• base: For frequencies that evenly subdivide 1 day, the "origin" of the aggregated intervals.
• on: column to use in case not the index is passed
• level: usually used for multiindex DataFrames

Let us understand with the help of an example,

Python Example of Pandas DataFrame.resample() Method

# Importing pandas package
import pandas as pd

# Creating dictionary
d = {
    'shape':['Cone','Sphere','Cylinder','Cube','Frustum'],
    'Volume':[213,389,545,200,589],
    'Area':[178,219,200,100,250]
}

# Creating DataFrame
df = pd.DataFrame(d,index=pd.date_range('09/16/2022',
                   periods=5,freq='W'))

# Display Original DataFrames
print("Created DataFrame:\n",df,"\n")

# Using resample method
res = df.Volume.resample('M').mean()

# Display Result
print("Result:\n",res)

Output

The output of the above program is:

Reference: pandas.DataFrame.resample

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