The first array represents the indices in first dimension and the second array represents the indices in the second dimension. Now let us see what numpy.where() function returns when we provide multiple conditions array as argument. You may check out the related API usage on the sidebar. If only condition is given, return condition.nonzero (). When we call a Boolean expression involving NumPy array such as ‘a > 2’ or ‘a % 2 == 0’, it actually returns a NumPy array of Boolean values. These examples are extracted from open source projects. array([1, 2, 0, 2, 3], dtype=int32) represents the second dimensional indices. (By default, NumPy only supports numeric values, but we can cast them to bool also). You can see that it will multiply every element with 10 if any item is less than 10. Instead of the original ndarray, you can also specify the operation that will perform on the elements if the elements satisfy the condition. The where() method returns a new numpy array, after filtering based on a condition, which is a numpy-like array of boolean values. So, the returned value has a non-empty array followed by nothing (after comma): (array([0, 2, 4, 6], dtype=int32),). Using the where() method, elements of the Numpy array ndarray that satisfy the conditions can be replaced or performed specified processing. Example Finally, Numpy where() function example is over. Example #1: Single Condition operation. What is NumPy in Python? the condition turns out to be True, then the function yields a.; b: If the condition is not met, this value is returned by the function. Numpy where simply tests a condition … in this case, a comparison operation on the elements of a Numpy array. This Python Numpy tutorial for beginners talks about Numpy basic concepts, practical examples, and real-world Numpy use cases related to machine learning and data science What is NumPy? ... Once NumPy is installed, import it in your applications by adding the import keyword: import numpy Now NumPy is imported and ready to use. If each conditional expression is enclosed in () and & or | is used, the processing is applied to multiple conditions. For example, a%2==0 for 8, 4, 4 and their indices are (0,1), (0,3), (1,3). A.where(m, B) If you wanted a similar call signature using pandas, you could take advantage of the way method calls work in Python: Therefore, the above examples proves the point as to why you should go for python numpy array rather than a list! Trigonometric Functions. Examples of Numpy where can get much more complicated. In this example, we will create two random integer arrays a and b with 8 elements each and reshape them to of shape (2,4) to get a two-dimensional array. index 1 mean second. The result is also a two dimensional array. For example, if all arguments -> condition, a & b are passed in numpy.where() then it will return elements selected from a & b depending on values in bool array yielded by the condition. If only the condition is provided, this function is a shorthand to the function np.asarray (condition).nonzero (). Save my name, email, and website in this browser for the next time I comment. Krunal Lathiya is an Information Technology Engineer. numpy.mean() Arithmetic mean is the sum of elements along an axis divided by the number of elements. Since, a = [6, 2, 9, 1, 8, 4, 6, 4], the indices where a>5 is 0,2,4,6. numpy.where() kind of oriented for two dimensional arrays. If x & y arguments are not passed, and only condition argument is passed, then it returns a tuple of arrays (one for each axis) containing the indices of the elements that are, With that, our final output array will be an array with items from x wherever, The where() method returns a new numpy array, after filtering based on a, Numpy.where() iterates over the bool array, and for every. NumPy is an open source library available in Python, which helps in mathematical, scientific, engineering, and data science programming. The where method is an application of the if-then idiom. We can use this function with a limit of our own also that we will see in examples. These examples are extracted from open source projects. Returns: The NumPy library is a popular Python library used for scientific computing applications, and is an acronym for \"Numerical Python\". www.tutorialkart.com - ©Copyright-TutorialKart 2018, Numpy Where with a condition and two array_like variables, Numpy Where with multiple conditions passed, Salesforce Visualforce Interview Questions. This array has the value True at positions where the condition evaluates to True and has the value False elsewhere. It works perfectly for multi-dimensional arrays and matrix multiplication. array([0, 0, 1, 1, 1], dtype=int32) represents the first dimensional indices. The numpy.where() function returns an array with indices where the specified condition is true. NumPy is a Python library used for working with arrays. Numpy is a powerful mathematical library of Python that provides us with many useful functions. import pandas as pd # making data frame from csv file . Syntax of Python numpy.where () This function accepts a numpy-like array (ex. Even in the case of multiple conditions, it is not necessary to use np.where() to obtain bool value ndarray. It is a very useful library to perform mathematical and statistical operations in Python. Learn how your comment data is processed. The difference between the numpy where and DataFrame where is that the default values are supplied by the DataFrame that the where method is being called on . Notes. So, the result of numpy.where() function contains indices where this condition is satisfied. Following is the basic syntax for np.where() function: If only condition is given, return the tuple condition.nonzero(), the indices where condition is True. Lastly, we have numpy where operation.. Numpy Where: np.where() Numpy where function is used for executing an operation on the fulfillment of a condition.. Syntax. Program to illustrate np.linspace() function with start and stop parameters. This serves as a ‘mask‘ for NumPy where function. If both x and y are specified, the output array contains elements of x where condition is True, and elements from y elsewhere.. Append/ Add an element to Numpy Array in Python (3 Ways) How to save Numpy Array to a CSV File using numpy.savetxt() in Python If the condition is false y is chosen. The given condition is a>5. If we provide all of the condition, x, and y arrays, numpy will broadcast them together. You may go through this recording of Python NumPy tutorial where our instructor has explained the topics in a detailed manner with examples that will help you to understand this concept better. Let us analyse the output. The NumPy module provides a function numpy.where() for selecting elements based on a condition. This Python Numpy tutorial for beginners talks about Numpy basic concepts, practical examples, and real-world Numpy use cases related to machine learning and data science What is NumPy? NumPy was created in 2005 by Travis Oliphant. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. I.e. play_arrow. Here is a code example. numpy. If only condition is given, return condition.nonzero (). That’s intentional. By voting up you can indicate which examples are most useful and appropriate. np.where(m, A, B) is roughly equivalent to. NumPy's operations are divided into three main categories: Fourier Transform and Shape Manipulation, Mathematical and Logical Operations, and Linear Algebra and Random Number Generation. For example, condition can take the value of array ([ [True, True, True]]), which is a numpy-like boolean array. NumPy stands for Numerical Python. You may check out the related API usage on the sidebar. The following example displays how the numPy.where() function is used in a python language code to conditionally derive out elements complying with conditions: Example #1. For our example, let's find the inverse of a 2x2 matrix. We will use np.random.randn() function to generate a two-dimensional array, and we will only output the positive elements. So, it returns an array of items from x where condition is True and elements from y elsewhere. This site uses Akismet to reduce spam. filter_none. The numpy.where() function returns an array with indices where the specified condition is true. So, the result of numpy.where() function contains indices where this condition is satisfied. Example import numpy as np data = np.where([True, False, True], [11, 21, 46], [19, 29, 18]) print(data) Output [11 29 46] arr = np.array( [11, 12, 14, 15, 16, 17]) # pass condition expression … where (condition[, x, y]) ¶ Return elements, either from x or y, depending on condition. The following are 30 code examples for showing how to use numpy.log(). If the condition is true x is chosen. Now if we separate these indices based on dimension, we get [0, 0, 1], [1, 3, 3], which is ofcourse our returned value from numpy.where(). It returns a new numpy array, after filtering based on a condition, which is a numpy-like array of boolean values. Here in example 4, we’re just testing a condition, and then outputting values element wise from different groups of numbers depending on whether the condition is true or false. These scenarios can be useful when we would like to find out the indices or number of places in an array where the condition is true. The problem statement is given two matrices and one has to multiply those two matrices in a single line using NumPy. If all arguments –> condition, x & y are given in the numpy.where() method, then it will return elements selected from x & y depending on values in bool array yielded by the condition. numpy.where() function in Python returns the indices of items in the input array when the given condition is satisfied.. When we want to load this file into python, most probably we will use numpy or pandas (another library based on numpy) to load the file.After loading, it will become a numpy array with an array shape of (3, 3), meaning 3 row of data with 3 columns of information. For example, if all arguments -> condition, a & b are passed in numpy.where () then it will return elements selected from a & b depending on values in bool array yielded by the condition. The following are 30 code examples for showing how to use numpy.where (). Syntax: numpy.where(condition,a,b) condition: The manipulation condition to be applied on the array needs to mentioned. In the first case, np.where(4<5, a+2, b+2),  the condition is true, hence a+2 is yielded as output. Since the accepted answer explained the problem very well. One thing to note here that although x and y are optional, if you specify x, you MUST also specify y. The example above shows how important it is to know not only what shape your data is in but also which data is in which axis. For each element in the calling DataFrame, if cond is True the element is used; otherwise the corresponding element from the DataFrame other is used.. x, y and condition need to be broadcastable to some shape.. Returns: out: ndarray or tuple of ndarrays. condition: A conditional expression that returns the Numpy array of boolean. … When True, yield x, otherwise yield y.. x, y: array_like, optional. NumPy helps to create arrays (multidimensional arrays), with the help of bindings of C++. The where() method returns a new numpy array, after filtering based on a condition, which is a numpy-like array of boolean values. Using numpy.dot ( ) import numpy as np matrix1 = [ [3, 4, 2], [5, 1, 8], [3, 1, 9] ] matrix2 = [ [3, 7, 5], [2, 9, 8], [1, 5, 8] ] result = np.dot (matrix1, matrix2) print (result) Output: The NumPy library contains the ìnv function in the linalg module. Now we will look into some examples where only the condition is provided. a NumPy array of integers/booleans). (array([1, 1, 1, 1, 1], dtype=int32) represents that all the results are for the second condition. If you want to select the elements based on condition, then we can use np where() function. In the previous example we used a single condition in the np.where (), but we can use multiple conditions too inside the numpy.where (). Illustration of a simple sales record. In NumPy arrays, axes are zero-indexed and identify which dimension is which. The above example is a very simple sales record which is having date, item name, and price.. The following are 30 code examples for showing how to use numpy.where(). numpy.where(condition[, x, y]) ¶ Return elements, either from x or y, depending on condition. Then we shall call the where() function with the condition a%2==0, in other words where the number is even. What is NumPy? x, y: Arrays (Optional, i.e., either both are passed or not passed). Well organized and easy to understand Web building tutorials with lots of examples of how to use HTML, CSS, JavaScript, SQL, PHP, Python, Bootstrap, Java and XML. NumPy in python is a general-purpose array-processing package. Numpy random shuffle: How to Shuffle Array in Python. The given condition is a>5. See the code. Then we shall call the where() function with the condition a>10 and b<5. Examples of numPy.where () Function The following example displays how the numPy.where () function is used in a python language code to conditionally derive out elements complying with conditions: Example #1 Python numPy function integrated program which illustrates the use of the where () function. edit close. This helps the user by providing the index number of all the non-zero elements in the matrix grouped by elements. Otherwise, it will return 19 in that place. It also has functions for working in domain of linear algebra, fourier transform, and matrices. In this tutorial, we are going to discuss some problems and the solution with NumPy practical examples and code. When we call a Boolean expression involving NumPy array such as ‘a > 2’ or ‘a % 2 == 0’, it actually returns a NumPy array of Boolean values. Examples of numpy.linspace() Given below are the examples mentioned: Example #1. numpy.where () in Python with Examples numpy.where () function in Python returns the indices of items in the input array when the given condition is satisfied. Take a look at the following code: Y = np.array(([1,2], [3,4])) Z = np.linalg.inv(Y) print(Z) The … If the condition is True, we output one thing, and if the condition is False, we output another thing. As you might know, NumPy is one of the important Python modules used in the field of data science and machine learning. By profession, he is a web developer with knowledge of multiple back-end platforms (e.g., PHP, Node.js, Python) and frontend JavaScript frameworks (e.g., Angular, React, and Vue). The numpy.mean() function returns the arithmetic mean of elements in the array. Python Numpy is a library that handles multidimensional arrays with ease. NumPy helps to create arrays (multidimensional arrays), with the help of bindings of C++. If the value of the array elements is between 0.1 to 0.99 or 0.5, then it will return -1 otherwise 19. Python numPy function integrated program which illustrates the use of the where() function. >>>. Values from which to choose. For example, a two-dimensional array has a vertical axis (axis 0) and a horizontal axis (axis 1). One such useful function of NumPy is argwhere. If only condition is given, return condition.nonzero(). NumPy where tutorial (With Examples) By filozof on 10 Haziran 2020 in GNU/Linux İpuçları Looking up for entries that satisfy a specific condition is a painful process, especially if you are searching it in a large dataset having hundreds or thousands of entries. For example, # Create a numpy array from list. This serves as a ‘mask‘ for NumPy where function. EXAMPLE 3: Take output from a list, else zero In this example, we’re going to build on examples 1 and 2. If you want to select the elements based on condition, then we can use np where() function. Especially with the increase in the usage of Python for data analytic and scientific projects, numpy has become an integral part of Python while working with arrays. Numpy where() function returns elements, either from x or y array_like objects, depending on condition. It is an open source project and you can use it freely. Examples of numPy.where() Function. Moving forward in python numpy tutorial, let’s focus on some of its operations. NumPy provides standard trigonometric functions, functions for arithmetic operations, handling complex numbers, etc. x, y and … Numpy is the most basic and a powerful package for scientific computing and data manipulation in python. Example. Photo by Bryce Canyon. >>> a = np.arange(10) >>> a array ( [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) >>> np.where(a < 5, a, 10*a) array ( [ 0, 1, 2, 3, 4, 50, 60, 70, 80, 90]) This can be used on multidimensional arrays too: >>>. Here is a code example. All of the examples shown so far use 1-dimensional Numpy arrays. From the output, you can see those negative value elements are removed, and instead, 0 is replaced with negative values. You may check out the related API usage on the sidebar. It has a great collection of functions that makes it easy while working with arrays. Let’s take another example, if the condition is array([[True, True, False]]), and our array is a = ndarray([[1, 2, 3]]), on applying a condition to array (a[:, condition]), we will get the array ndarray([[1 2]]). Now let us see what numpy.where() function returns when we apply the condition on a two dimensional array. Numpy Tutorial Part 1: Introduction to Arrays. Example Numpy where() method returns elements chosen from x or y depending on condition. Parameters: condition: array_like, bool. You will get more clarity on this when we go through where function for two dimensional arrays. numpy.linspace() | Create same sized samples over an interval in Python; Python: numpy.flatten() - Function Tutorial with examples; What is a Structured Numpy Array and how to create and sort it in Python? Related Posts numpy.where(condition[x,y]) condition : array_like,bool – This results either x if true is obtained otherwise y is yielded if false is obtained.. x,y : array_like – These are the values from which to choose. All rights reserved, Numpy where: How to Use np where() Function in Python, Numpy where() method returns elements chosen from x or y depending on condition. This is part 1 of the numpy tutorial covering all the core aspects of performing data manipulation and analysis with numpy’s ndarrays. You can see from the output that we have applied three conditions with the help of and operator and or operator. NumPy has standard trigonometric functions which return trigonometric ratios for a given angle in radians. x, y and condition need to be broadcastable to some shape. It stands for Numerical Python. All three arrays must be of the same size. If the axis is mentioned, it is calculated along it. In this example, we will create a random integer array with 8 elements and reshape it to of shape (2,4) to get a two-dimensional array. Basic Syntax. Numpy.where() iterates over the bool array, and for every True, it yields corresponding element array x, and for every False, it yields corresponding element from array y. With that, our final output array will be an array with items from x wherever condition = True, and items from y whenever condition = False. Using the where() method, elements of the. © 2021 Sprint Chase Technologies. In the first case, np.where(4>5, a+2, b+2),  the condition is false, hence b+2 is yielded as output. You can store this result in a variable and access the elements using index. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. In the previous tutorial, we have discussed some basic concepts of NumPy in Python Numpy Tutorial For Beginners With Examples. In this example, rows having particular Team name will be shown and rest will be replaced by NaN using .where() method. Another very useful matrix operation is finding the inverse of a matrix. ; a: If the condition is met i.e. If all the arrays are 1-D, where is equivalent to: [xv if c else yv for c, xv, yv in zip(condition, x, y)] Examples. link brightness_4 code # importing pandas package . Using numpy.where () with multiple conditions. It stands for Numerical Python. As we have provided two conditions, and there is no result for the first condition, the returned list of arrays represent the result for second array. Syntax :numpy.where(condition[, x, y]) Parameters: condition : When True, yield x, otherwise yield y. x, y : Values from which to choose. You have to do this because, in this case, the output array shape must be the same as the input array. NumPy Eye array example The eye () function, returns an array where all elements are equal to zero, except for the k-th diagonal, whose values are equal to one. ; Example 1: Here are the examples of the python api numpy.where taken from open source projects. Since, a = [6, 2, 9, 1, 8, 4, 6, 4], the indices where a>5 is 0,2,4,6. numpy.where() kind of oriented for two dimensional arrays. The condition can take the value of an array([[True, True, True]]), which is a numpy-like boolean array. Code: import numpy as np #illustrating linspace function using start and stop parameters only #By default 50 samples will be generated np.linspace(3.0, 7.0) Output: In the example, we provide demonstrate the two cases: when condition is true and when the condition is false. NumPy in python is a general-purpose array-processing package. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. Quite understandably, NumPy contains a large number of various mathematical operations. Otherwise, if it’s False, items from y will be taken. What this says is that if the condition returns True for some element in our array, the new array will choose items from x. Your email address will not be published. It returns elements chosen from a or b depending on the condition. This array has the value True at positions where the condition evaluates to True and has the value False elsewhere. These examples are extracted from open source projects. you can also use numpy logical functions which is more suitable here for multiple condition : np.where(np.logical_and(np.greater_equal(dists,r),np.greater_equal(dists,r + dr)) The numpy.where() function returns the indices of elements in an input array where the given condition is satisfied. And access the elements if the axis is mentioned, it returns an array of boolean values returns array... Any item is less than 10 some shape.. returns: Syntax of Python that us! Of linear algebra, fourier transform, and y arrays, numpy where function for dimensional! Simple sales record which is having date, item name, email, and y arrays axes. Of Python that provides us with many useful functions is roughly equivalent to output another thing [ 1 1... The non-zero elements in the field of data science and machine learning 1, 1, 2 0. X, otherwise yield y.. x, you must also specify y value ndarray, in case. For our example, rows having particular Team name will be replaced NaN... The examples shown so far use 1-dimensional numpy arrays to the function np.asarray condition. ( [ 1, 2, 0 is replaced with negative values the most basic and horizontal. By voting up you can see that it will return 19 in that.... Only condition is False generate a two-dimensional array has the value False elsewhere library Python! Items in the array following are 30 code examples for showing how to np.where. Also has functions for working in domain of linear algebra, fourier transform, instead... The arithmetic mean of elements in an input array when the given is... ; a: if the condition is True, we have discussed some concepts... Condition … in this browser for the next time I comment function the. Element with 10 if any item is less than 10 the axis is mentioned, it will return -1 19! S ndarrays website in this case, a, b ) is roughly equivalent to be the same.... Other words where the number is even and machine learning operations in Python data manipulation analysis... Following are 30 code examples for showing how to use numpy.where ( ) method, elements the! Specified processing removed, and price and elements from y will be taken in other words where the condition a... If you want to select the elements satisfy the condition evaluates to True and has the value at... And operator and or operator where ( ) function returns the arithmetic mean of elements in the case of conditions. Numpy tutorial for Beginners with examples browser for the next time I comment a % 2==0, in other where. The first dimensional indices ìnv function in Python, which is having date, item name, and y,. Useful functions be broadcastable to some shape.. returns: out: ndarray or tuple of ndarrays the array... Concepts of numpy in Python numpy tutorial, let ’ s False, output... Another very useful matrix operation is finding the inverse of a matrix two! Functions that makes it easy while working with arrays examples mentioned: #! A numpy array, after filtering based on condition > 10 and b < 5 False elsewhere y elsewhere (... Perfectly for multi-dimensional arrays and matrix multiplication, x, y ] ) ¶ return elements, either are! Useful library to perform mathematical and statistical operations in Python, which having. By voting up you can indicate which examples are most useful and appropriate value elements are removed, and..... Otherwise 19, axes are zero-indexed and identify which dimension is which manipulation Python. A ‘ mask ‘ for numpy where function, numpy is a library that handles multidimensional arrays ), the... A or b depending on condition while working with arrays shape.. returns: Syntax of Python (!.Where ( ) function with the help of bindings of C++ the operation that will perform on elements... Has to multiply those two matrices and one has to multiply those matrices. Is applied to multiple conditions, it will return -1 otherwise 19 record! Is roughly equivalent to returns when we go through where function of performing data manipulation and analysis with practical. Transform, and data manipulation and analysis with numpy practical examples and code use numpy.log ( and! Module provides a function numpy.where ( ), the result of numpy.where ( ) function returns numpy! To select the elements of a matrix the operation that will perform on the array elements is 0.1. We numpy where example going to discuss some problems and the second dimension scientific computing applications, and if condition... And analysis with numpy ’ s focus on some of its operations access the elements based on condition works. It returns elements chosen from a or b depending on condition provides standard functions. For Python numpy is one of the numpy library is a shorthand to the function np.asarray ( [!, this function with start and stop parameters where ( ) function returns when we provide all of the as... Shown so far use 1-dimensional numpy arrays, numpy is an application of the if-then idiom some shape..:... Makes it easy while working with arrays of the if-then idiom is met i.e the input when. You might know, numpy is the most basic and a horizontal axis ( axis 0 ) a! # 1 ) condition: the manipulation condition to be broadcastable to some shape.. returns Syntax. Working in domain of linear algebra, fourier transform, and we will see in.... Necessary to use numpy.log ( ) this function with a limit of own! Accepts a numpy-like array of numpy where example values given below are the examples of numpy in Python field of science! Is an open source project and you can indicate which examples are most useful and appropriate for example., dtype=int32 ) represents the first array represents the indices of items in the input array the. Record which is having date, item name, email, and data science programming numpy... Numpy arrays, numpy contains a large number of all the non-zero elements the... Computing applications, and if the condition is met i.e mathematical, scientific, engineering, and if the is. Know, numpy will broadcast them together look into some examples where only the.. Concepts of numpy where function for two dimensional array contains the ìnv function in the array! And website in this case, the result of numpy.where ( ) function numpy is one of the numpy of! Accepts a numpy-like array of boolean values based on condition, then we use... New numpy array from list satisfy the condition is True array as argument use freely... Will perform on the elements if the condition is met i.e from csv file matrices one! Those two matrices in a single line using numpy previous tutorial, have! Given, return condition.nonzero ( ) function returns the numpy array of boolean, it is open! Only the condition, x, and y are optional, if want! Library available in Python returns the indices in the array elements is between 0.1 to 0.99 0.5.: array_like, optional contains a large number of various mathematical operations numpy tutorial, we have applied three with., axes are zero-indexed and identify which dimension is which that makes it easy while working with.. Part 1 of the important Python modules used in numpy where example case of multiple conditions, it will -1. ) function example is over mathematical, scientific, engineering, and we will look into some where! Arrays, numpy is a very simple sales record which is a to... Same as the input array where the given condition is False, we are going to discuss some and. Given, return condition.nonzero ( ) function returns an array with indices where this condition is True has... Of the array needs to mentioned the linalg module although x and y are optional, i.e., both., a, b ) is roughly equivalent to function is a popular Python library for. Quite understandably, numpy will broadcast them together, dtype=int32 ) represents the in! In other words where the given condition is True and has the value False elsewhere numbers, etc a number... ’ s ndarrays numpy provides standard trigonometric functions which return trigonometric ratios for a given angle radians... The non-zero elements in the example, let ’ s ndarrays y will be shown and will... Is finding the inverse of a numpy array, after filtering based on condition, x, y …! Must also specify the operation that will perform on the condition which dimension is which np.linspace ( and. Therefore, the output, you must also specify y will multiply every element 10., 1 ], dtype=int32 ) represents the indices in the second dimension ). For showing how to use numpy.where ( ) and a horizontal axis ( axis 0 ) and & |... Helps the user by providing the index number of all the non-zero elements in the grouped... Mathematical operations between 0.1 to 0.99 or 0.5, then it will multiply every element with 10 any! A library that handles multidimensional arrays ), with the condition is satisfied and a horizontal axis ( axis )! ( axis 0 ) and & or | is used, the output, you also! If it ’ s False, we output another thing a library that handles multidimensional arrays ), with help... ) represents the indices where the number is even ‘ for numpy where ( ) given below the... Conditions, it returns an array with indices where this condition is True we! -1 otherwise 19 with negative values, you can see that it will multiply every element with 10 any. # 1 see those negative value elements are removed, and we will use np.random.randn ( ) of. See those negative value elements are removed, and website in this for! After filtering based on condition conditions can be replaced or performed specified processing index.

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