In this Python blog, I will explainhow to get unique values in an array using the NumPy unique function in Python. I will explain different use cases for the NumPy unique function likenp.uniquewithout sorting, NumPy unique with tolerance, etc. To get unique values in an array, we can use...
importnumpyasnp# 定义一个包含重复值的数组arr=np.array([1,2,3,4,2,3,1,5])# 使用numpy的unique函数找到不同的值unique_values=np.unique(arr)# 输出结果print(unique_values) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 运行以上代码,输出结果为:[1 2 3 4 5]。可以看到,通过numpy的unique函数找...
d = da.from_array(a, chunks=(3,)) r_a = np.unique(a, **kwargs) r_d = da.unique(d, **kwargs)ifnotany([return_index, return_inverse, return_counts]):assertisinstance(r_a, np.ndarray)assertisinstance(r_d, da.Array) r_a = (r_a,) r_d = (r_d,)assertlen(r_a) == ...
A commonly used one is np.unique, which returns the sorted unique values in an array: In [206]: names = np.array(['Bob', 'Joe', 'Will', 'Bob', 'Will', 'Joe', 'Joe']) In [207]: np.unique(names) Out[207]: array(['Bob', 'Joe', 'Will'], dtype='<U4') In [208]:...
foreleinnp.unique(li): res.append(ele) # Calculating the length to get the count of unique elements count =len(res) print("The count of unique values in the list:", count) # The count of unique values in the list: 4 Another approach is to create an array using thearray()function ...
In [160]: import matplotlib.pyplot as plt In [161]: plt.imshow(z, cmap=plt.cm.gray);plt.colorbar() Out[161]: <matplotlib.colorbar.Colorbar at 0x7f715e3fa630> In [162]: plt.title("Image plot of $\sqrt{x^2 + y^2}$ for a grid of values") ...
index/columns/values,分别对应了行标签、列标签和数据,其中数据就是一个格式向上兼容所有列数据类型的array。为了沿袭字典中的访问习惯,还可以用keys()访问标签信息,在series返回index标签,在dataframe中则返回columns列名;可以用items()访问键值对,但一般用处不大。
array([[[1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1]], [[1, 1, 1, 1], [1, 1, 1, 1], [1, 1, 1, 1]]], dtype=int16) (4)np.empty >>> # Create an empty array with 2 elements >>> np.empty(2)
Unique Values, Value Counts, and Membership# series.value_counts()计算元素个数; series.isin([])计算 series 中是否存在所说的元素,返回一个 boolean series; series.unique()返回 series 中 unique 的元素 series; Conclusion# In the next chapter, we’ll discuss tools for reading (or loading) and ...
# 2. 使用当前narray的原生的属性进行操作 np_int_array = np_array.astype(np.int32) print("当前去重的操作后的结果为:{}".format(np.unique(np_int_array))) # 使用当前的第一种方式实现当前数组的数据的去重操作 one_way_array = np_int_array.flatten() ...