- Trending Categories
Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
Physics
Chemistry
Biology
Mathematics
English
Economics
Psychology
Social Studies
Fashion Studies
Legal Studies
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
Return the cumulative sum of array elements over given axis 0 treating NaNs as zero in Python
To return the cumulative sum of array elements over a given axis treating NaNs as zero, use the nancumprod() method. The cumulative sum does not change when NaNs are encountered and leading NaNs are replaced by zeros. Zeros are returned for slices that are all-NaN or empty. Cumulative works like, 5, 5+10, 5+10+15, 5+10+15+20.
The 1st parameter is the input array. The 2nd parameter is the axis along which the cumulative sum is computed. The default (None) is to compute the cumsum over the flattened array. The 3rd parameter is the type of the returned array and of the accumulator in which the elements are summed. If dtype is not specified, it defaults to the dtype of a, unless a has an integer dtype with a precision less than that of the default platform integer. In that case, the default platform integer is used. The 4th parameter is the alternative output array in which to place the result. It must have the same shape and buffer length as the expected output but the type will be cast if necessary.
Steps
At first, import the required library −
import numpy as np
Creating a numpy array using the array() method. We have added elements of int type with nan −
arr = np.array([[10, 20, 30], [40, np.nan, 60]])
Display the array −
print("Our Array...\n",arr)Check the Dimensions −
print("\nDimensions of our Array...\n",arr.ndim)
Get the Datatype −
print("\nDatatype of our Array object...\n",arr.dtype)To return the cumulative sum of array elements over a given axis treating NaNs as zero, use the nancumprod() method −
print("\nCumulative Sum of array elements...\n",np.nancumsum(arr, axis = 0))Example
import numpy as np
# Creating a numpy array using the array() method
# We have added elements of int type with nan
arr = np.array([[10, 20, 30], [40, np.nan, 60]])
# Display the array
print("Our Array...\n",arr)
# Check the Dimensions
print("\nDimensions of our Array...\n",arr.ndim)
# Get the Datatype
print("\nDatatype of our Array object...\n",arr.dtype)
# To return the cumulative sum of array elements over a given axis treating NaNs as zero, use the nancumprod() method
# The cumulative sum does not change when NaNs are encountered and leading NaNs are replaced by zeros.
# Zeros are returned for slices that are all-NaN or empty.
print("\nCumulative Sum of array elements...\n",np.nancumsum(arr, axis = 0))Output
Our Array... [[10. 20. 30.] [40. nan 60.]] Dimensions of our Array... 2 Datatype of our Array object... float64 Cumulative Sum of array elements... [[10. 20. 30.] [50. 20. 90.]]
88 Views
