Numpy&Pandas快速上手篇

Numpy&Pandas

Numpy篇

Numpy 创建array

import numpy as np

# a = np.array([1,2,3], dtype =np.int )# a = np.array([[1,2,3],[3,4,5]] , dtype =float )  #设置精度中 设置64只能用np.float64# a = np.zeros((3,5),dtype = np.int64)# a = np.ones((3,4), dtype = np.int64)# a = np.empty((3,4), dtype = np.int16)# a = np.empty((3,4))# a = np.full((3,4),2) #指定矩阵的全部值# a = np.arange(10,20)# a = np.arange(20)# a = np.arange(20).reshape((5,4))

a = np.linspace(1,5,20).reshape((5,4))# 线段， 从1到10分段print(a)print(a.dtype)
a.fill(2)# 也可以直接用numpy 中的fill填充2print(a)# print(help(np.empty))

Numpy属性

import numpy as np

a = np.array([[1,2,3],[5,9,8]])print(a)print("number of dim:", a.ndim)# 维度print("shape:", a.shape)print("size:", a.size)

Num基本运算1

import numpy as np

## #a = np.array([1,11,1])# a = np.array([[1,11,1],[2,3,4]])### b = np.arange(6).reshape(3,2)### print(a<5) #判断逻辑符直接输出bool型# print(a ==5)## print(a)# print(b)## #c = a*b //数和数相乘 前提：同型矩阵# #c = b**2# #c =a - b# #c = a -b# #c = np.dot(a,b) //矩阵相乘 或者# #c = a.dot(b)# #c = np.cos(a) * 100### print(c)

a = np.random.random((2,4))# print(np.max(a))# print(np.sum(a))# print(np.min(a))print(np.max(a, axis=0))# axis轴 为1 为行 0为列print(np.sum(a, axis=1))print(np.min(a, axis=1))print(a)

Numpy基本运算2

import numpy as np

a = np.arange(15,3,-1).reshape((3,4))print(np.argmax(a))# 最大值索引 argument of a functionprint(np.argmin(a))# 最小值索引# 平均值(也可以设置按行列求）print(np.mean(a))print(a.mean())# 老版本print(np.average(a))# 不支持# print(a.average)# 中位数print(np.median(a))# 累加前面的值print(np.cumsum(a))# Cumulative sum 积累 和# 输出非0的行和列print(np.nonzero(a))# 两数之差print(np.diff(a))# 每一行(列）排序print(np.sort(a, axis=0))# 转置print(np.transpose(a))print(a.T.dot(a))# 只留下范围内的值print(np.clip(a,5,9))print(a)

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