cumprod pandas example | pandas cumprod skipna | pandas cumprod across columns
In this pandas tutorial, we will discuss about:
-
pandas cumprod method,
-
cumprod pandas example
Before going ahead with understanding pandas cumprod method and cumprod pandas example lets have little knowledge about pandas dataframe.
DataFrame in pandas is a two dimensional data structure that will store data in two dimensional format. One dimension refers to a row and second dimension refers to a column, So It will store the data in rows and columns.
We can create this DataFrame using DataFrame() method. But this is available in pandas module, so we have to import pandas module.
Syntax:
pandas.DataFrame(data)
Where, data is the input dataframe, the data can be a dictionary that stores list of values with specified key.
Example: Create dataframe
In this example, we will create a dataframe with 4 rows and 3 columns with building data and assign indices through index parameter.
import pandas as pd
#create dataframe from the building data
data= pd.DataFrame({
'length':[5.6,7.8,4.5,5.3],
"breadth":[12.9,4.5,21.5,6.0],
"area":[20,56,43,45]
},index=['one','two','three','four'])
#display the dataframe
print(data)
Output: Dataframe is created
length breadth area
one 5.6 12.9 20
two 7.8 4.5 56
three 4.5 21.5 43
four 5.3 6.0 45
Lets use this dataframe to understand cumprod pandas example.
Pandas cumprod
pandas cumprod() will return the cumulative product of values for the given dataframe.
Syntax:
dataframe.cumprod(axis,skipna)
This will return the entire dataframe
Parameters:
-
axis=0 specifies row and axis= 1 specifies column to get cumulative product along row/column
-
pandas cumprod skipna will take boolean values - True or False. If False,It will consider NaN values and If True,It will not consider NaN values in cumulative product operation.
If we want to get the cumulative product of values in a column for the given dataframe, we have to specify the column.
Syntax:
dataframe['column'].cumprod()
where, dataframe is the input dataframe and column is the column name.
Pandas cumprod across columns will return the specified column cumulative product in the given dataframe.
Lets now see few cumprod pandas example.
cumprod pandas example: pandas cumprod across columns
In this cumprod pandas example, we will get the cumulative product for the entire dataframe and in a specific column.
import pandas as pd
#create dataframe from the building data
data= pd.DataFrame({
'length':[5.6,7.8,4.5,5.3],
"breadth":[12.9,4.5,21.5,6.0],
"area":[20,56,43,45]
},index=['one','two','three','four'])
# get the cumulative product
print(data.cumprod())
print()
# get the cumulative product from length column
print(data['length'].cumprod())
print()
# get the cumulative product from area column
print(data['area'].cumprod())
Output: cumprod pandas example result is shown below
length breadth area
one 5.600 12.900 20
two 43.680 58.050 1120
three 196.560 1248.075 48160
four 1041.768 7488.450 2167200
one 5.600
two 43.680
three 196.560
four 1041.768
Name: length, dtype: float64
one 20
two 1120
three 48160
four 2167200
Name: area, dtype: int64
Lets now see pandas cumprod skipna example.
cumprod pandas example: pandas cumprod skipna
In this pandas cumprod skipna example. we will be dealing with skipna parameter.
import pandas as pd
import numpy as np
#create dataframe from the building data
data= pd.DataFrame({
'length':[np.nan,7.8,4.5,np.nan],
"breadth":[12.9,4.5,21.5,np.nan],
"area":[2,np.nan,56,43]
},index=['one','two','three','four'])
# get the cumulative product with out nan values
print(data.cumprod(skipna=True))
print()
# get the cumulative product by considering nan values
print(data.cumprod(skipna=False))
Output: pandas cumprod skipna example result is shown below
length breadth area
one NaN 12.900 2.0
two 7.8 58.050 NaN
three 35.1 1248.075 112.0
four NaN NaN 4816.0
length breadth area
one NaN 12.900 2.0
two NaN 58.050 NaN
three NaN 1248.075 NaN
four NaN NaN NaN
Thus we have learned about cumprod pandas example for both pandas cumprod skipna and pandas cumprod across columns.
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About the Author
Gottumukkala Sravan Kumar 171FA07058
B.Tech (Hon's) - IT from Vignan's University.
Published 800+ Technical Articles on Python, R, Java, C#, LISP, PHP - MySQL and Machine Learning
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Published Date :
Apr 07,2022