returns index positionnp.where(y>5)array([2, 3, 5, 7, 8], dtype=int64),)# First will replace the values that match the condition,# second will replace the values that does notnp.where(y>5, "Hit", "Miss")array(['Miss', 'Miss', 'Hit...
We can directly substitute the array instead of the iterable variable in our condition and it will work just as we expect it to.Example Create a filter array that will return only values higher than 42: import numpy as nparr = np.array([41, 42, 43, 44]) filter_arr = arr > 42new...
array([2, 3, 5, 7, 8], dtype=int64) # First will replace the values that match the condition, # second will replace the values that does not >>> np.where(y>5, "Hit", "Miss") array(['Miss', 'Miss', 'Hit', 'Hit', 'Miss', 'Hit', 'Miss', 'Hit', 'Hit'], dtype='<...
NumPy 初学者指南中文第三版:6~10 NumPy: Beginner’s Guide - Third Edition协议:CC BY-NC-SA 4.0译者:飞龙 六、深入探索 NumPy 模块 NumPy 具有许多从其前身 Numeric 继承的模块。 其中一些包具有 SciPy 对应版本,可能具有更完整的功能。 我们将在下一章中讨论 SciPy。 在本章中,我们将介绍以下主题: linal...
y = np.array([1,5,6,8,1,7,3,6,9])# Where y is greaterthan 5, returns index position np.where(y>5)array([2, 3, 5, 7, 8], dtype=int64),)# First will replace the values that matchthe condition,# second will replace the values that does not np.where(y>5, "Hit", "...
np.extract(((array<3) | (array>15)),array) array([0,1,19,16,18,2]) where Where 用于从一个数组中返回满足特定条件的元素。比如,它会返回满足特定条件的数值的索引位置。Where 与 SQL 中使用的 where condition 类似,如以下示例所示: y = np.array([1,5,6,8,1,7,3,6,9])# Where y is...
array([ 1, 19, 11, 13, 3])# Apply condition on extract directly np.extract(((array 《 3) | (array 》 15)), array) array([ 0, 1, 19, 16, 18, 2]) 5、where() Where() 用于从一个数组中返回满足特定条件的元素。比如,它会返回满足特定条件的数值的索引位置。Where() 与 SQL 中使用...
NumPy array to a string in Python NumPy array to a List of Strings in Python How NumPy Filter 2D Array by Condition in Python I am Bijay Kumar, aMicrosoft MVPin SharePoint. Apart from SharePoint, I started working on Python, Machine learning, and artificial intelligence for the last 5 ye...
A = np.array([[ 7, 0 , 6 , 0 , 4 , 0 , 9, 0, 7215, 7215],\ [ 1, 8, 1, 2, 1, 9, 1, 3, 7215, 7215], [ 1 , 5 , 1, 8, 7215, 7215, 7215, 7215, 7215, 7215], [ 1 , 8 , 1, 9, 7215, 7215, 7215, 7215, 7215, 7215], ...
na_filter=True, verbose=False, skip_blank_lines=True, parse_dates=False, infer_datetime_format=False, keep_date_col=False, date_parser=None, dayfirst=False, iterator=False, chunksize=None, compression='infer', thousands=None, decimal=b'.', lineterminator=None, quotechar='"', quoting=0, ...